Commoditizing the Enterprise
david1962Chapter 2 Quality Management
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In this chapter, you will learn about...
• What Is Quality?
• Quality Management System
• Quality Tools
• TQM and QMS
• The Focus of Quality Management—Customers
• The Role of Employees in Quality Improvement
• Quality in Services
• Six Sigma
• The Cost of Quality
• The Effect of Quality Management on Productivity
• Quality Awards
• ISO 9000
Quality Management AT MARS
Mars produces its chocolate candy products according to five principles that define a philosophy of its values that lead and guide the company. First among these principles is quality. At Mars “the consumer is the boss; quality is the work; and value is the goal.” Their commitment to quality guides their approach to delivering products that “delight their customers” while meeting uncompromising safety standards.
The Mars Quality Management Process (QMP) is applied to all aspects of its supply chain, from acquiring high-quality ingredients, to their manufacturing processes, to product distribution, and to measuring customer satisfaction. Mars QMP is maintained at the leading edge of quality management practices by benchmarking against the highest quality and food safety standards and best practices throughout the food industry. Continuous improvement is the foundation of Mars QMP and drives the company to continually raise its standards and learn how to do things more effectively and efficiently to bring value to its customers.
In effect, quality is an obsession at Mars. All Mars employees are committed to quality, are provided the technical skills to deliver quality excellence, and are accountable for providing their customers with the highest possible quality. An example is their fear of “incremental degradation,” a term they use to describe what can happen by using cheaper ingredients. Rather than replace a high-priced ingredient with a cheaper one, even if taste tests show that the customer wouldn't notice the difference, Mars will forego the extra profit to avoid risking incremental degradation in product quality. In spotlessly clean Mars plants, employees are constantly tasting products to make sure they are being made properly, and an entire production run of Snickers may be thrown out because of barely noticeable nicks in the chocolate coating. A Mars salesman at a supermarket will throw out a whole product display if it's getting too close to its freshness date. Mars considers each individual sale its most important one, and their goal is to build life-long relationships with its customers. They believe if they forget this they risk resting on their past and ignoring their future.
In this chapter we will discuss how other quality-conscious companies like Mars develop effective quality management [QM] programs.
Source: Mars Web site at www.mars.com; and Craig J. Cantoni, “Manager's Journal: Quality Control from Mars,” Wall Street Journal, January 27, 1992, pg. A12.
WHAT IS QUALITY?
Asked “What is quality?” one of our students replied “getting what you pay for.” Another student added that to her, quality was “getting more than you paid for!” The Oxford American Dictionary defines quality as “a degree or level of excellence.”
What is quality in the eye of the beholder?
The American Society for Quality (ASQ) defines quality as “a subjective term for which each person has his or her own definition. In technical usage, quality can have two meanings: (1) The characteristics of a product or service that bear on its ability to satisfy stated or implied needs and (2) A product or service free of deficiencies.” Obviously, quality can be defined in many ways, depending on who is defining it and the product or service it refers to. In this section we provide a perspective on what quality means to customers and companies.
QUALITY FROM THE CUSTOMER'S PERSPECTIVE
A business organization produces goods and services to meet its customers' needs. Customers want value and quality has become a major factor in the value of products and service. Customers know that certain companies produce better-quality products than others, and they buy accordingly. That means a firm must consider how the consumer defines quality. The customer can be a manufacturer purchasing raw materials or parts, a store owner or retailer purchasing products to sell, or someone who purchases retail products or services over the Internet. W. Edwards Deming, author and consultant on quality, says that “The consumer is the most important part of the production line. Quality should be aimed at the needs of the consumer, present and future.” From this perspective, product and service quality is determined by what the customer wants and is willing to pay for. Since customers have different product needs, they will have different quality expectations. This results in a commonly used definition of quality as a service's or product's fitness for its intended use, or fitness for use; how well does it do what the customer or user thinks it is supposed to do and wants it to do?
Fitness for use:
is how well the product or service does what it is supposed to.
Products and services are designed with intentional differences in quality to meet the different wants and needs of individual consumers. A Mercedes and a Ford truck are equally “fit for use,” in the sense that they both provide automobile transportation for the consumer, and each may meet the quality standards of its individual purchaser. However, the two products have obviously been designed differently for different types of consumers. This is commonly referred to as the quality of design—the degree to which quality characteristics are designed into the product. Although designed for the same use, the Mercedes and Ford differ in their performance, features, size, and various other quality characteristics.
Quality of design:
involves designing quality characteristics into a product or service.
DIMENSIONS OF QUALITY FOR MANUFACTURED PRODUCTS
The dimensions of quality for manufactured products a consumer looks for include the following1:
Dimensions of manufactured quality for which a consumer looks.
1. Performance : The basic operating characteristics of a product: for example, how well a car handles or its gas mileage.
2. Features : The “extra” items added to the basic features, such as a stereo CD or a leather interior in a car.
3. Reliability : The probability that a product will operate properly within an expected time frame: that is, a TV will work without repair for about seven years.
4. Conformance : The degree to which a product meets preestablished standards.
5. Durability : How long the product lasts; its life span before replacement. A pair of L.L. Bean boots, with care, might be expected to last a lifetime.
6. Serviceability : The ease of getting repairs, the speed of repairs, and the courtesy and competence of the repair person.
7. Aesthetics : How a product looks, feels, sounds, smells, or tastes.
8. Safety : Assurance that the customer will not suffer injury or harm from a product: an especially important consideration for automobiles.
9. Other perceptions : Subjective perceptions based on brand name, advertising, and the like.
These quality characteristics are weighed by the customer relative to the cost of the product. In general, customers will pay for the level of quality they can afford. If they feel they are getting what they paid for (or more), then they tend to be satisfied with the quality of the product.
DIMENSIONS OF QUALITY FOR SERVICES
The dimensions of quality for a service differ somewhat from those of a manufactured product. Service quality is more directly related to time, and the interaction between employees and the customer. Evans and Lindsay2 identify the following dimensions of service quality.
Dimensions of service quality.
1. Time and timeliness : How long must a customer wait for service, and is it completed on time? For example, is an overnight package delivered overnight?
2. Completeness : Is everything the customer asked for provided? For example, is a mail order from a catalogue company complete when delivered?
3. Courtesy : How are customers treated by employees? For example, are catalogue phone operators at L.L. Bean nice and are their voices pleasant?
4. Consistency : Is the same level of service provided to each customer each time? Is your newspaper delivered on time every morning?
5. Accessibility and convenience : How easy is it to obtain the service? For example, when you call L.L. Bean does the service representative answer quickly?
6. Accuracy : Is the service performed right every time? Is your bank or credit card statement correct every month?
7. Responsiveness : How well does the company react to unusual situations, which can happen frequently in a service company? For example, how well is a telephone operator at L.L. Bean able to respond to a customer's questions about a catalogue item not fully described in the catalogue?
A Mercedes and a Ford pickup truck are equally “fit for use,” but with different design dimensions for different customer markets that result in significantly different purchase prices.
1 Adapted from D. A. Garvin. “What Does Quality Really Mean?” Sloan Management Review 26(1: 1984). pp. 25-43.
2 J. R. Evans and W. M. Lindsay, The Management and Control of Quality, 3rd ed. (St. Paul, MN: West, 1996).
QUALITY FROM THE PRODUCER'S PERSPECTIVE
Now we need to look at quality the way a producer or service provider sees it: how value is created. We already know that product development is a function of the quality characteristics (i.e the product's fitness for use) the customer wants, needs, and can afford. Product or service design results in design specifications that should achieve the desired quality. However, once the product design has been determined, the producer perceives quality to be how effectively the production process is able to conform to the specifications required by the design referred to as the quality of conformance . What this means is quality during production focuses on making sure that the product meets the specifications required by the design.
Quality of conformance:
is making sure the product or service is produced according to design.
Achieving quality of conformance involves design, materials and equipment, training, supervision, and control.
Examples of the quality of conformance: If new tires do not conform to specifications, they wobble. If a hotel room is not clean when a guest checks in, the hotel is not functioning according to the specifications of its design; it is a faulty service. From this producer's perspective, good-quality products conform to specifications—they are well made; poor-quality products are not made well—they do not conform to specifications.
Achieving quality of conformance depends on a number of factors, including the design of the production process (distinct from product design), the performance level of machinery, equipment and technology, the materials used, the training and supervision of employees, and the degree to which statistical quality-control techniques are used. When equipment fails or is maladjusted, when employees make mistakes, when material and parts are defective, and when supervision is lax, design specifications are generally not met. Key personnel in achieving conformance to specifications include the engineering staff, supervisors and managers, and, most important, employees.
An important consideration from the customer's perspective of product quality is product or service price. From the producer's perspective, an important consideration is achieving quality of conformance at an acceptable cost. Product cost is also an important design specification. If products or services cannot be produced at a cost that results in a competitive price, then the final product will not have acceptable value—the price is more than the consumer is willing to pay given the product's quality characteristics. Thus, the quality characteristics included in the product design must be balanced against production costs.
L.L. Bean's first product was the Maine Hunting shoe, developed in 1912 by company founder, Leon Leonwood Bean, a Maine outdoorsman. He initially sold 100 pairs to fellow sportsmen through the mail, but 90 pairs were sent back when the stitching gave way. However, true to his word L.L. Sean returned their money and started over with an improved boot. In years to come L.L. Bean operated his business according to the following belief: “Sell good merchandise at a reasonable profit, treat your customers like human beings, and they will always come back for more.” L.L. Bean also guarantees their products to “give 100% satisfaction in every way,” If they don't, L.L. Bean will replace the item or refund the purchase price “at any time.”
A FINAL PERSPECTIVE ON QUALITY
We approached quality from two perspectives, the customer's and the producer's. These two perspectives are dependent on each other as shown in Figure 2.1. Although product design is customer-motivated, it cannot be achieved without the coordination and participation of the production process. When a product or service is designed without considering how it will be produced, it may be impossible for the production process to meet design specifications or it may be so costly to do so that the product or service must be priced prohibitively high.
Figure 2.1 depicts the meaning of quality from the producer's and consumer's perspectives. The final determination of quality is fitness for use, which is the customer's view of quality. It is the consumer who makes the final judgment regarding quality, and so it is the customer's view that must dominate.
Figure 2.1 The Meaning of Quality
QUALITY MANAGEMENT SYSTEM
To make sure that products and services have the quality they have been designed for, strategy to achieve quality throughout the organization is required. This approach to the management of quality throughout the entire organization has evolved into what is generally referred to as a quality management system (QMS).
THE EVOLUTION OF QUALITY MANAGEMENT
A handful of prominent individuals summarized in Table 2.1 have had a dramatic impact on the importance of quality in the United States, Japan, and other countries. Of these “quality gurus” W. Edwards Deming has been the most prominent.
In the 1940s Deming worked at the Census Bureau, where he introduced the use of statistical process control to monitor the mammoth operation of key punching data from census questionnaires onto millions of punch cards. During World War II, Deming developed a national program of 8- and 10-day courses to teach statistical quality-control techniques to over 10.000 engineers at companies that were suppliers to the military during the war. By the end of World War II he had an international reputation.
In 1950 Deming began teaching statistical quality control to Japanese companies. As a consultant to Japanese industries and as a teacher, he was able to convince them of the benefits of statistical quality control. He is a major figure in the Japanese quality movement, and in Japan he is frequently referred to as the father of quality control
In the 1950s, W. E. Deming began teaching quality control in Japan.
Table 2.1 Quality Gurus
Quality Guru
Contribution
Walter Shewhart
Working at Bell Laboratories in the 1920s. he developed the technical tools such as control charts that formed the basis of statistical quality control; he and his colleagues at Bell Labs introduced the term quality assurance for their program to improve quality through the use of statistical control methods.
W. Edwards Deming
A disciple of Shewart, he developed courses during World War II to teach statistical quality-control techniques to engineers and executives of companies that were military suppliers; after the war he began teaching statistical quality control to Japanese companies, initiating their quality movement.
Joseph M. Juran
An author and consultant, he followed Deming to Japan in 1954; he focused on strategic quality planning within an annual qualify program, setting goals for product quality and designing processes to achieve those goals: quality improvement is achieved by focusing on projects to solve problems and securing breakthrough solutions.
Armand V. Feigenbaum
In his 1951 book, Quality Control: Principles, Practices and Administration, he introduced the concept of total quality control and continuous quality improvement as a companywide strategic commitment requiring the involvement of all functions in the quality process, not just manufacturing; discovered by Japanese in the 1950s at about the same time as Juran's visit: from 1958 to 1968 he was director of manufacturing operations and quality control at GE.
Philip Crosby
In his 1979 book, Quality Is Free, he emphasized that the costs of poor quality (including lost labor and equipment time, scrap, downtime and lost sales) far outweigh the cost of preventing poor quality: in his 1984 book, Quality Without Tears, he defined absolutes of quality management—quality is defined as conformance to requirements, quality results from prevention, the performance standard is “zero defects.”
Kaoru Ishikawa
This Tokyo University professor promoted use of quality circles and developed the ‘fishbone’ (cause and effect) diagram to diagnose quality problems; he emphasized the importance of the internal customer, that is, that a quality organization is first necessary in order to produce quality products or services.
• Inernet Exercises
Deming's approach to quality management advocated contineous improvement of the production process to achieve conformance to specifications and reduce variability. He identified two primary sources of process improvement: eliminating common causes of quality problems, such as poor product design and insufficient employee training, and eliminating special causes, such as specific equipment or an operator. Deming emphasized the use of statistical quality-control techniques to reduce variability in the production process. He dismissed the then widely-used approach of final product inspection as a means of ensuring good quality as coming too late to reduce product defects. Primary responsibility for quality improvement, he said, was employees' and management's. He promoted extensive employee involvement in a quality improvement program, and he recommended training for workers in quality-control techniques and methods.
Deming's overall philosophy for achieving improvement is embodied in his 14 points, summarized in Table 2.2.
Deming is also credited for development of the Deming Wheel, or plan-do-check-act (PDCA) cycle, although it was originally formulated by Walter Shewhart and renamed by the Japanese.
W. E. Deming is the most famous of all “quality gurus.” He introduced statistical quality control to the Japanese, which served as the catalyst for a worldwide quality movement. His “14 points” were the foundation for modem TQM and QMS processes.
The Deming Wheel—plan, do. check, act.
Table 2.2 W.E. Deming's 14 points
1. Create a constancy of purpose toward product improvement to achieve long-term organizational goals.
2. Adopt a philosophy of preventing poor-quality products instead of acceptable levels of poor quality as necessary to compete internationally.
3. Eliminate the need for inspection to achieve quality by relying instead on statistical quality control to improve product and process design.
4. Select a few suppliers or vendors based on quality commitment rather than competitive prices.
5. Constantly improve the production process by focusing on the two primary sources of quality problems, the system and employees, thus increasing productivity and reducing costs.
6. Institute worker training that focuses on the prevention of quality problems and the use of statistical quality-control techniques.
7. Instill leadership among supervisors to help employees perform better.
8. Encourage employee involvement by eliminating the fear of reprisal for asking questions or identifying quality problems.
9. Eliminate barriers between departments, and promote cooperation and a team approach for working together.
10. Eliminate slogans and numerical targets that urge employees to achieve higher performance levels without first showing them how to do it.
11. Eliminate numerical quotas that employees attempt to meet at any cost without regard for quality.
12. Enhance worker pride, artisanry, and self-esteem by improving supervision and the production process so that employees can perform to their capabilities.
13. Institute vigorous education and training programs in methods of quality improvement throughout the organization, from top management down, so that continuous improvement can occur.
14. Develop a commitment from top management to implement the previous 13 points.
The Deming Wheel is a four-stage process for continuous quality improvement that complements Deming's 14 points, as shown in Figure 2.2.
Deming's approach to quality embodied in his 14 points and PDCA cycle are the foundation for today's quality management systems employed by many successful companies.
Figure 2.2 The Deming Wheel (PDCA Cycle)
ALONG THE SUPPLY CHAIN Applying Deming's PDCA Cycle in Baldrige Award-Winning Schools and Hospitals
Jenks Public Schools (JPS), a 2005 recipient of the prestigious Malcolm Baldrige National Quality Award, serves 9,400 students with nine schools in the city of Jenks and portions of Tulsa, Oklahoma. The school district's continuous quality improvement model is based on the work of W. E. Deming, and a central part of its model was its application of Deming's PDCA cycle to procedures related to key performance measures, such as improving test scores. All staff members participate in the district's goal setting process and incorporate the PDCA cycle into their plans for achieving these goals. The PDCA process provided a systematic approach for continuous improvement in teaching, learning, student achievement, and student and faculty well-being. It also supported process efficiency and effectiveness. As a result of its improvement efforts its teacher turnover rate for 2004 was 6% as compared to the national average of 20%; its academic performance scores exceeded state and national levels; 37% of the district's class of 2004 earned an AP test score of 3 or better compared to 13% nationally and 21 percent in the state; and its dropout rate was only slightly over 1%.
Baptist Hospital. Inc. (BHI), which includes hospitals in Pensacola and Gulf Breeze, Florida with 2.270 employees, was a recipient of the 2003 Malcolm Baldrige Award. One of the primary quality improvement tools used by BHI was Deming's PDCA cycle. BHI used several metrics to determine if hospital processes were maintaining organizational value. If any of the metrics fell below target values, a PDCA team made up of physicians and front-line employees was quickly initiated to address the deficiencies using the PDCA process. In various surveys and health databases BHI's patient care, patient satisfaction, emergency department and ambulatory surgery, as well as other health-related areas, ranked well ahead of benchmarked programs.
Iredell-Statesville Schools located in southwestern North Carolina with 21,000 students in 35 schools was a 2008 Baldrige Award Winner. Despite ranking 107 out of 115 school systems in North Carolina in per pupil expenditures, it ranked in the top 10 in the state in academic achievement; its average SAT scores ranked seventh in the state and were better than the national average; its graduation rate was 81%; its attendance rate of 96% ranked third in the state; and its teacher turnover rate was well below the state average. As part of its continuous quality improvement program called the “Model to Raise Achievement and Close Gaps (RACG).” it establishes targets in key classroom learning categories. When student performance does not meet the targets in a school the gap is addressed using the PDCA cycle to develop and implement improvements, which are then shared with other schools in the district.
Mercy Health System, a 2007 Baldrige Award recipient, includes three hospitals, a network of 64 facilities, and nearly 4,000 employees serving six counties in southern Wisconsin and northern Illinois. The PDCA cycle is used in all quality improvement projects at Mercy. In one specific project, customer satisfaction with the emergency department at its hospital in Janesville. Wisconsin, fell below 93%, and a group was created to develop an action plan for improvement. The drop in satisfaction was determined to be caused by an increase in patient volume resulting from intermingling urgent care and emergency room patients. This resulted in a misperception that patients who came in later were seeing medical staff sooner than those already waiting, when, in fact, they were from two different groups; some were urgent care patients and others were emergency room patients. The quick solution was to move urgent care out of the emergency room, which required a capital expenditure. In addition it was determined that urgent care patients expect to be seen within 30 minutes, so this was established as a service goal and a tracking mechanism was established to make sure it was being met. PDCA was considered to be such a valuable tool in this process because it wasn't overwhelming or mysterious to the physicians, nurses, and managers involved in improvement projects.
In these examples the PDCA cycle is used in four service organizations; can you think of specific processes in a service organization you are familiar with that the PDCA cycle might be applied to, perhaps even your own university?
Sources: S. Daniels, “Oklahoma School District Goes Over the Top.” Quality Progress 39 (5; May 2006). pp. 51-59: K. Johnson. “Two Hospitals Improve Performance.” Quality Progress 37 (9: September 2004), pp. 46-55; S. Daniels, “Eyes on the Dashboard at Mercy Health System,” Quality Progress 41 (4; April 2008), pp. 42-44; and National Quality Program at the National Institute of Standards and Technology Web site http://www.quality.nist.gov.
QUALITY TOOLS
The seven well-known tools for identifying quality problems and their causes are sometimes called the “magnificent seven.”
A major cornerstone of the commitment to quality improvement prescribed by Deming and the other early quality gurus is the need to identity and prevent the causes of quality problems, or defects. These individuals prescribed a number of “tools” to identify the causes of quality problems that are still widely used today, including Pareto charts, process flowcharts, checksheets, histograms, scatter diagrams, statistical process control charts and cause-and-effect diagrams. In fact, as noted previously. Deming traveled to Japan primarily to teach statistical process control techniques. These popular tools became the basis for the quality management programs developed by many companies. In this section we will briefly describe some of these tools, which are summarized in Figure 2.3.
Figure 2.3 Quality Tools
• Inernet Exercises
A flowchart is a diagram of a job operation or process.
PROCESS FLOWCHARTS
A process flowchart is a diagram of the steps in a job, operation, or process. It enables everyone involved in identifying and solving quality problems to have a clear picture of how a specific operation works and a common frame of reference. It also enables a process improvement team to understand the interrelationship of the departments and functions that constitute a process. This helps focus on where problems might occur and if the process itself needs fixing. Development of the flowchart can help identify quality problems by helping the problem solvers better understand the process. Flowcharts are described in greater detail in Chapter 6 (“Processes and Technology”) and Chapter 8 (“Human Resources”).
process flowchart:
a diagram of the steps in a job, operation, or process.
CAUSE-AND-EFFECT DIAGRAMS
A cause-and-effect diagram, also called a fishbone or Ishikawa diagram, is a graphical description of the elements of a specific quality problem and the relationship between those elements. It is used to identify the causes of a quality problem so it can be corrected. Cause-and-effect diagrams are usually developed as part of brainstorming to help a quality team of employees and managers identify causes of quality problems.
Cause-and-effect diagram or fishbone diagram:
a chart showing the different categories of problem causes.
Figure 2.4 is a cause-and-effect diagram for a Six Sigma project at a hospital to reduce delays in patient bed turnaround time, which creates a patient flow problem throughout the hospital. The primary cause of the problem is suspected to be related to the “bed tracking system” (BTS), an electronic system that indicates the status of each bed to the registered nurse (RN) who admits patients and assigns them to a room. (See the “Along the Supply Chain” box for the North Shore University Hospital on page 79.)
The “effect” box at the end of the diagram is the quality problem that needs correction. A center line connects the effect box to the major categories of possible problem causes, displayed as branches off of the center line. The box at the end of each branch (or fishbone) describes the cause category. The diagram starts out in this form with only the major categories at the end of each branch. Individual causes associated with each category are attached as separate lines along the length of the branch during the brainstorming process. Sometimes the causes are rank-ordered along the branches in order to identify those that are most likely to affect the problem. The cause-and-effect diagram is a means for thinking through a problem and recording the possible causes in an organized and easily interpretable manner.
Figure 2.4 A Cause-and-Effect Diagram
Figure 2.5 A Cause-and-Effect Matrix
A complementary tool related to the fishbone diagram is the cause-and-effect matrix, which is used to prioritize the potential causes of quality problems in a process that might first be identified using a cause-and-effect diagram. The output (or Y) variables are listed along the top of the matrix. These are also referred to as CTQs or CTQCs. (i.e., “critical-to-quality characteristics”) and they are measurable characteristics that express the key requirements defined by a customer. CTQCs are what the customer expects from a product, and accordingly they have a significant impact on customer satisfaction. The input (or X) variables that might affect the outcome of process, (i.e., the potential causes of an outcome) are listed along the left side of the matrix (or grid). The CTQCs are ranked or weighted in terms of importance to the customer; then, the relationship between causes and effects (CTQs) are weighted or ranked; and finally, an overall score is calculated for the causes (or X variables). The causes with the highest score should be addressed first in improvement efforts because they will have the largest impact on customer satisfaction. Figure 2.5 shows a cause-and-effect matrix for the hospital bed turnaround time example. Note that staff communication has the highest score, and thus, the greatest impact on how satisfied the customers are with the overall process.
Cause-and-effect matrix:
grid used to prioritize causes of quality problems.
CHECKSHEETS AND HISTOGRAMS
Checksheets are frequently used in conjunction with histograms, as well as with Pareto diagrams. A checksheet is a fact-finding tool used to collect data about quality problems. A typical check sheet for quality defects tallies the number of defects for a variety of previously identified problem causes. When the check sheet is completed, the total tally of defects for each cause can be used to create a histogram or a Pareto chart, as shown in Figure 2.6.
A check sheer is a list of causes of quality problems with the number of defects resulting front each cause used to develop a bar chart called a histogram.
PARETO ANALYSIS
Pareto analysis is a method of identifying the causes of poor quality. It was devised in the early 1950s by the quality expert Joseph Juran. He named this method after a nineteenth-century Italian economist, Vilfredo Pareto, who determined that a small percentage of the people accounted for most of the wealth. Pareto analysis is based on Juran's finding that most quality problems and costs result from only a few causes. For example, he discovered in a textile mill that almost 75% of all defective cloth was caused by only a few weavers, and in a paper mill he studied, more than 60% of the cost of poor quality was attributable to a single category of defects. Correcting the few major causes of most of the quality problems will result in the greatest cost impact.
Pareto analysis:
most quality problems result from a few causes.
Pareto analysis can be applied by tallying the number of defects for each of the different possible causes of poor quality in a product or service and then developing a frequency distribution from the data. This frequency distribution, referred to as a Pareto diagram, is a useful visual aid for focusing on major quality problems.
Figure 2.6 Pareto Chart
The quality problem for hospital bed turnaround time described in the previous section on cause-and-effect diagrams (Figure 2.4) in this case a defect is anytime the turnaround time exceeds 150 minutes for a patient out of a sample of 195 patients. Some of the causes of this problem are as follows.
Cause
Number of Defects
Percentage
Staff communication
83
64%
BTS system
17
13
Room cleaning
13
10
Beepers
7
6
Laundry
4
3
Patients
3
2
Family
3
2
130
100%
For each cause of poor quality, the number of defects attributed to that cause has been tallied. This information is then converted into the Pareto chart shown in Figure 2.6 above.
This Pareto chart identifies the major cause of poor quality to be poor staff communication. Correcting the problem will result in the greatest quality improvement. However, the other problems should not be ignored. Continual quality improvement is the long-term goal. The Pareto diagram simply identifies the quality problems that will result in the greatest immediate impact on quality improvement.
A scatter diagram is a graph showing how two process variables relate to each other.
SCATTER DIAGRAMS
Scatter diagrams graphically show the relationship between two variables, such as the brittleness of a piece of material and the temperature at which it is baked. One temperature reading should result in a specific degree of brittleness representing one point on the diagram. Many such points on the diagram visually show a pattern between the two variables and a relationship or lack of one. This diagram could be used to identify a particular quality problem associated with the baking process.
PROCESS CONTROL CHARTS AND STATISTICAL QUALITY CONTROL
We discuss control charts and other statistical quality-control methods in Chapter 3, “Statistical Process Control.” For now, it is sufficient to say that a control chart is a means for measuring if a process is doing what it is supposed to do, like a thermostat monitoring room temperature. It is constructed with a horizontal line through the middle of a chart representing the process average or norm. It also has a line below this center line representing a lower control limit and a line above it for the upper control limit. Samples from the process are taken over time and measured according to some attribute. In its simplest form, if the measurement is within the upper and lower control limits, the process is said to be in control and there is no quality problem, but if the measurement is outside the limits, then a problem probably exists and should be investigated and corrected.
Process control involves monitoring a production or service process using statistical quality-control methods.
Statistical quality-control methods such as the process control chart are important tools for quality improvement. Employees who are provided with extensive training in statistical quality-control methods, are able to identify quality problems and their causes and to make suggestions for improvement. (See the “Along the Supply Chain” box on page 79 to see how a control chart is used to monitor hospital bed turnaround times).
TQM AND QMS
Total quality management (TQM) has been the most prominent and visible approach to quality to evolve from the work of Deming and the early quality gurus. TQM originated in the 1980s as a Japanese-style management approach to quality improvement, and became very popular during the 1990s, being adopted by thousands of companies. Although it has taken on many meanings, it was (and still is) a philosophy for managing an organization centered on quality and customer satisfaction as “the” strategy for achieving long-term success. It requires the active involvement, participation and cooperation of everyone in the organization, and encompasses virtually all of its activities and processes. To achieve and sustain this pervasive focus on quality requires a significant long-term commitment on the part of the organization's leadership. Deming's 14 points and the philosophies and teachings of the early quality gurus are clearly embodied in the basic principles of TQM:
Total Quality Management (TQM):
customer-oriented, leadership, strategic planning, employee responsibility, continuous improvement, cooperation, statistical methods, and training and education.
1. Quality can and must be managed.
2. The customer defines quality, and customer satisfaction is the top goal: it is a requirement and is not negotiable.
3. Management must be involved and provide leadership.
4. Continuous quality improvement is “the” strategic goal, which requires planning and organization.
5. Quality improvement is the responsibility of every employee; all employees must be trained and educated to achieve quality improvement.
6. Quality problems are found in processes, and problems must be prevented, not solved.
7. The quality standard is “no defects.”
8. Quality must be measured; improvement requires the use of quality tools, and especially-statistical process control.
Quality Management System (QMS):
A system to to achieve customer satisfaction that complements other company systems.
TQM has been supplanted to a large extent by what is most commonly referred to as a quality management system (QMS) . This approach (or term) has evolved out of the ISO certification process that many companies around the world have gone through; essentially ISO certifies a company's “quality management system.” and much of the ISO's written materials refer directly to “quality management systems.” (ISO certification is discussed in greater detail in a separate section later in this chapter.) A QMS is not as much of a philosophy as TQM: rather, it is a system that complements a company's other systems and functions. It is a systematic approach to achieving quality and hence customer satisfaction, and while it suggests no less commitment to that goal than TQM, it maintains less of a core strategic focus that TQM. Further, since a QMS is not a “philosophy.” it more naturally is designed to meet the individual needs and circumstances of a particular company. It outlines the policies and procedures necessary to improve and control specific (but not all) processes that will lead to improved business performance. A QMS tends to focus more on individual projects that have a quantifiable impact (i.e., increased profitability). Some companies have adopted the Malcolm Baldrige National Quality Award criteria as its QMS; another well-known QMS is Six Sigma (which we will discuss in greater detail in a later section).
Regardless of the term a company uses to identify its approach to achieving quality improvement, and the possible differences between TQM and a QMS or other approaches, there are certain common characteristics of company-wide approaches to quality improvement, such as customer satisfaction and employee involvement, topics we will talk about next.
THE FOCUS OF QUALITY MANAGEMENT—CUSTOMERS
The main focus of Deming's 14 points, TQM and all QMSs is to achieve customer satisfaction. The reason is simple; customers who are very happy and delighted are less likely to switch to a competitor, which translates to profits. A high level of satisfaction creates an emotional bond instead of simply a rational preference. Research by companies has shown that there is a direct link between customer satisfaction and attrition rates, indicating that delighted customers are less likely to defect than dissatisfied customers. Figure 2.7 highlights some of the “facts” that are generally known to exist about customer satisfaction.
Figure 2.7 The Impact of Customer Satisfaction
QUALITY MANAGEMENT IN THE SUPPLY CHAIN
Most companies not only have customers they want to satisfy, but they are also customers of other companies, their suppliers, within a company's supply chain. Companies know that to satisfy its customers requires not only their own commitment to quality, but also the support and resources of its suppliers. This is especially true of companies that outsource many of their activities to suppliers. Companies and their suppliers joined together in a supply chain must work together to meet the needs of the company's customers. A partnership exists between the supplier and its customer wherein the supplier is expected to manage its own quality effectively so that the company it supplies can count on the quality of the materials, parts, and services it receives.
Many companies reduce their number of suppliers in order to have more direct influence over their suppliers' quality and delivery performance, which was one of Deming's 14 points. It is based on the notion that if a company has a major portion of a supplier's business, then the supplier is more willing to meet the customer's quality standards. The company and supplier enter into a business relationship referred to as partnering, in which the supplier agrees to meet the company's quality standards, and in return the company enters into a long-term purchasing agreement with the supplier that includes a stable order and delivery schedule.
In order to ensure that its supplier meets its quality standards, a company will often insist that the supplier adopt a QMS similar to its own, or a company's QMS will include its suppliers. Still other companies require that their suppliers achieve ISO 9000 certification (see page 95), an international quality standard that ensures a high industry standard of quality as its QMS; some companies require their suppliers to follow Baldrige National Quality Award guidelines or even enter the Baldrige Award competition as their QMS.
At the other end of a company's spectrum from its suppliers is its direct relationship with its own customers. An important component of any QMS is the company's ability to measure customer satisfaction; to “hear” what the customer wants. The company needs to know if its QMS is effective. Is the company meeting customer expectations? Are its products or services meeting their fitness for use definition? Is it what the customer wants, does the customer like it, does the customer need it, would the customer like it changed? A QMS requires that some form of measurement system be in place to answer these questions and provide data about the customer's level of satisfaction. It is a well-established fact of consumer behavior that unhappy customers will tell almost twice as many others about their quality problems as they will tell others about satisfactory products or services.
Partnering:
a relationship between a company and its supplier based on mutual quality standards.
MEASURING CUSTOMER SATISFACTION
For most companies, figuring out what satisfies customers (i.e., what they want and need) is easier said than done. It requires that a company somehow gather information on what the customer wants and needs, disseminate that information throughout the company, use that information to improve its products and processes and develop new products, and then monitor customer satisfaction to ensure that the customer's needs are being met. The primary means for garnering information from customers, and measuring customer satisfaction is the customer survey. The customer survey is a means for companies to listen to what is often referred to as the “voice of the customer (VoC).” Applicants for the Malcolm Baldrige National Quality Award are expected to provide measures of customer satisfaction typically through customer surveys. Motorola, a two-time Baldrige Award winner, contracts with an independent survey firm to conduct regularly scheduled surveys with its customers around the world to help Motorola determine how well it's meeting its customers' needs.
J.D. Power and Associates is an independent, third-party, company that provides companies in the automotive, energy/communications, travel, financial, and home-building industries with feed back from their customers based on surveys that they conduct. They also annually present awards to companies that have excelled in their industry based on independently financed consumer opinion studies. Award-winning companies are allowed to license the use of J.D. Power and Associates awards in advertising. For example, their 2006 automotive performance award winner for the “large car” was the Hyundai Azera: their 2006 award winner for the “highest guest satisfaction among mid-scale hotel chains” was Hampton Inns.
• Inernet Exercises
The American Customer Satisfaction Index (ACSI) was established in 1994 through a partnership of the University of Michigan Business School, the American Society for Quality (ASQ), and the international consulting firm, CFI Group. The ACSI is funded in part by corporate subscribers who receive industry benchmarking data and company-specific information about financial returns from improving customer satisfaction.
ACSI measures customer satisfaction with the goods and services of 7 economic sectors. 39 industries (including e-commerce and e-business), and more than 200 companies and 70 federal and local government agencies. The ACSI reports scores on a 0 to 100 scale, which are based on econometric modeling of data obtained from telephone interviews with customers. From random-digit-dial (RDD) telephone samples (and Internet samples for e-commerce and e-business), more than 65,000 consumers are identified and interviewed annually.
ACSI scores are posted on their Web site at www.theacsi.org. For example, in 2008 Amazon.com had an ACSI score of 86, one of the highest scores ever recorded in any service industry. Apple was the leading company in the computer industry with a score of 85. Lexus and BMW were the highest-scoring car companies at 87, followed by Toyota and Honda at 86.
ALONG THE SUPPLY CHAIN Measuring Customer Satisfaction with “Voice of the Customer [VoC]” at Two Baldrige Award Winners
The U.S. Army Armament Research, Development and Engineering Center (ARDEC), a 2007 recipient of the Baldrige National Quality Award, develops 90% of the Army's armaments and ammunition such as firearms, explosives, warheads, and advanced hi-tech weaponry. ARDEC, headquartered in Picatinny Arsenal, New Jersey, has nearly 3,000 employees and annual net revenues over $1 billion. In addition to serving the Army, its customers include the U.S. Special Operations Command and the Department of Homeland Security. It has been applying Baldrige criteria since the 1990s, and since 2005 it has used such practices as Lean Six Sigma and ISO 9000 to continually improve its processes and its products, which has resulted in a 91% increase in quality, a reduction in cost of 70%. improved scheduling of 67%, and overall cost avoidance of $3.22 billion. In addition, ARDEC's customer satisfaction ratings, a key Baldrige criterion, increased from 3.48 (on a 4-point scale) in 2000 to 3.75 in 2007. This increase is primarily a result of its “Voice of the Customer (VoC)” program.
Measuring customer satisfaction is literally a matter of life and death for an organization like ARDEC; the security of the United States and the safety of its soldiers depend on ARDEC's ability to continually improve and achieve the highest quality possible. ARDEC's VoC program includes a 400-person conference with soldiers just returned from the war zone who talk about what worked (and didn't work) for them in the field. The discussion also leads to possible innovations; products are designed for one thing, but soldiers get creative and often find out they work for something else. ARDEC's quick reaction task force (QRTF) also developed a formal process using a Web-based tracking tool that gathers questions and needs from soldiers in the field, and works quickly to develop quick answers and solutions. In a nine-month period in 2006-2007 responses to 80% of soldier inquiries were developed in less than 72 hours, which contributed to customer satisfaction ratings well above government best-in-class benchmarks. Other Web-based survey tools generate over 60 pages of comments every quarter that are immediately accessible to everyone in the organization.
Poudre Valley Health System (PVHS), a 2008 Baldrige Award recipient, also uses a VoC program to gauge customer satisfaction. PVHS is a not-for-profit health-care organization headquartered in Fort Collins, Colorado, serving Colorado, Nebraska, and Wyoming residents, with annual revenues over $330 million and a workforce of 4,000. According to various surveys, PVHS patient loyalty ranks in the top 1% of U.S. hospitals, overall physician satisfaction ranks in the 99th percentile in the nation, is consistently in the top 10% of national performance standards for treating heart failure and pneumonia, and consistently maintains lower health-care charges than its competitors.
PVHS actively involves its customer through its VoC program to provide guidance for strategic planning, goal setting, and quality improvement initiatives. In one instance customer input was incorporated in the planning and building of its newest hospital, the Medical Center of the Rockies, including the layout of emergency rooms, patient room window views (with most facing the mountains), healing gardens, and family amenities such as showers and kitchens.
Examples were given of how each of these organizations used VoC tools to assess customer satisfaction. What other tools do you think they (or other organizations) might employ to get customer feedback?
Sources: B. Krzykowski “Customer Servicemen,” Quality Progress 41 (6; June 2008), pp. 30-34; and National Quality Program at the National Institute of Standards and Technology Web site, http://www.quality.nist.gov.
THE ROLE OF EMPLOYEES IN QUALITY IMPROVEMENT
Job training and employee development are major features of a successful quality management program. Increased training in job skills results in improved processes that improve product quality. Training in quality tools and skills such as statistical process control enable employees to diagnose and correct day-to-day problems related to their job. This provides employees with greater responsibility for product quality and greater satisfaction for doing their part to achieve quality. When achievement is reinforced through rewards and recognition, it further increases employee satisfaction. At Ritz-Carlton, first-year employees receive over 300 hours of training. Marriott employees are trained to view breakdowns in service as opportunities for satisfying customers; for example, they may send a gift and note of apology to customers who have experienced a problem in the hotel.
In our previous discussions, the importance of customer satisfaction as an overriding company objective was stressed. However, another important aspect of a successful QMS is internal customer (e.g., employee) satisfaction. It is unlikely that a company will be able to make its customers happy if its employees are not happy. For that reason, many successful companies conduct employee satisfaction surveys just as they conduct customer surveys.
When employees are directly involved in the quality management process, it is referred to as participative problem solving . Employee participation in identifying and solving quality problems has been shown to be effective in improving quality, increasing employee satisfaction and morale, improving job skills, reducing job turnover and absenteeism, and increasing productivity.
Participative problem solving:
employees are directly involved in the quality management process.
Participative problem solving is usually within an employee-involvement (El) program, with a team approach. We will look at some of these programs for involving employees in quality management, including kaizen, quality circles, and process improvement teams.
KAIZEN AND CONTINUOUS IMPROVEMENT
Kaizen is the Japanese term for continuous improvement, not only in the workplace but also in one's personal life, home life, and social life. In the workplace, kaizen means involving everyone in a process of gradual, organized, and continuous improvement. Every employee within an organization should be involved in working together to make improvements. If an improvement is not part of a continuous, ongoing process, it is not considered kaizen. Kaizen is most closely associated with lean systems, an approach to continuous improvement throughout the organization that is the subject of Chapter 16.
kaizen:
involves everyone in a process of continuous improvement.
Employees are most directly involved in kaizen when they are determining solutions to their own problems. Employees are the real experts in their immediate workspace. In its most basic form, kaizen is a system in which employees identify many small improvements on a continual basis and implement these improvements themselves. This is actually the application of the steps in the Deming Wheel (Figure 2.2) at its most basic, individual level. Employees identify a problem, come up with a solution, check with their supervisor, and then implement it. This works to involve all employees in the improvement process and gives them a feeling that they are really participating in quality improvement, which in turn keeps them excited about their jobs. Nothing motivates someone more than when they come up with a solution to their own problem. Small individual changes have a cumulative effect in improving entire processes, and with this level of participation improvement occurs across the entire organization. No company-wide quality management program can succeed without this level of total employee involvement in continuous improvement.
With today's foucs on healthcare costs, quality in healthcare is a major issue in the service sector. Its importance is signified by the fact that it is one of five categories in which the Baldrige National Quality Award is annually given.
Employees at Dana Corporation's Spicer Driveshaft Division, North America's largest independent manufacturer of driveshafts and a 2000 Malcolm Baldrige National Quality Award winner, participate in a kaizen-type program. On average, each employee submits three suggestions for improvements per month and almost 80 percent of these ideas are implemented. The company also makes use of kaizen “blitzes” in which teams brainstorm, identify, and implement ideas for improvement, sometimes as often as every three or four weeks. Company-wide, Dana Corporation employees implemented almost 2 million ideas in one year alone.
QUALITY CIRCLES
One of the first team-based approaches to quality improvement was quality circles . Called quality-control circles in Japan when they originated during the 1960s, they were introduced in the United States in the 1970s. A quality circle is a small, voluntary group of employees and their supervisor(s), comprising a team of about 8 to 10 members from the same work area or department. The supervisor is typically the circle moderator, promoting group discussion but not directing the group or making decisions; decisions result from group consensus. A circle meets about once a week during company time in a room designated especially for that purpose, where the team works on problems and projects of their own choice. These problems may not always relate to quality issues; instead, they focus on productivity, costs, safety, or other work-related issues in the circle's area. Quality circles follow an established procedure for identifying, analyzing, and solving quality-related (or other) problems. Figure 2.8 is a graphical representation of the quality circle process.
Quality circle:
a group of workers and supervisors from the same area who address quality problems.
Figure 2.8 The Quality Circle Process
A process improvement team includes members from the interrelated functions or departments that make up a process.
PROCESS IMPROVEMENT TEAMS
Process improvement teams, also called quality improvement teams (QIT), focuses attention on business processes rather than separate company functions. It was noted previously that quality circles are generally composed of employees and supervisors from the same work area or department, whereas process improvement teams tend to be cross-functional or even cross-business between suppliers and their customers. A process improvement team would include members from the various interrelated functions or departments that constitute a process. For example, a process improvement team for customer service might include members from distribution, packaging, manufacturing, and human resources. A key objective of a process improvement team is to understand the process the team is addressing in terms of how all the parts (functions and departments) work together. The process is then measured and evaluated, with the goal of improving the process to make it more efficient and the product or service better. A key tool in helping the team understand how the process works is a process flowchart, a quality tool we discussed in greater detail in the section on “Quality Tools.”
ALONG THE SUPPLY CHAIN Customer Focus and Employee Empowerment in a Baldrige Award-Winning City
Coral Springs, located in Broward County (north of Miami), is the 13th largest city in Florida with a population of over 132,000, a workforce of 770 full-time and 300 part-time employees, and an annual budget of $135 million. A 2007 recipient of the Baldrige National Quality Award, it is the first state or local government agency to do so. Operated much like a business, the city's quality management program is based on four core values: customer focus, leadership, empowered employees, and continuous improvement. Coral Springs' two-year strategic planning process, which sets objectives and its budget, is based on input from its customer base—residents and businesses. To provide information to its customers and get customer feedback it uses a call center and Web site, email, a city magazine, podcasts. CityTV, CityRadio, a consumer-friendly “City Hall in the Mall” (for bill payments permit applications), annual neighborhood meetings, 27 advisory committees and boards comprised of residents and business people, customer surveys, demographic trends, and analyses of strengths, weaknesses, and opportunities.
A key component of Coral Springs' success has been an empowered, motivated, and high-performing workforce. The city strives to retain its excellent staff through job security, competitive pay and benefits, a safe and positive work environment, and recognition programs. Employees are encouraged to be innovative and make “on-the-spot” improvements. Employee teams work together to solve problems and review processes. Employees are recognized and rewarded in several ways including “applause cards” given by one employee to another for exemplary customer service, restaurant and movie certificates for employees who display outstanding initiative, and bonuses for extraordinary service. For the past decade employee satisfaction was above 90%, and the turnover rate in 2006 was only 4.5%.
As a result of its quality improvement initiatives, Coral Springs' resident satisfaction is above 95%, and its business satisfaction is 97%. In 2006 Money magazine named it as one of the “Best Places to Live.” and during the past decade its crime rate dropped by nearly half; for a city its size it has the lowest crime rate in the state and the fourth lowest in the nation.
Since 2000 it has maintained a AAA credit rating from all three of the nation's largest bond rating agencies.
Compare the quality programs in the city you are from (or that your university is in) with the quality program in Coral Springs. How do you think your city stacks up against Coral Springs? What initiatives used in Coral Springs do you think would work in your city?
Sources: B. Krzykowski, Quality Progress 41 (6; June 2008), pp. 33-35; and National Quality Program at the National Institute of Standards and Technology Web site http://www.quality.nist.gov.
QUALITY IN SERVICES
From our discussion so far it is clear that most quality management approaches evolved in manufacturing companies like Toyota, GE, and Motorola. However, in the 1980s and 1990s service companies began to embrace quality management. This is important because the service sector is the largest segment of the U.S. economy, employing almost three times as many people as manufacturing industries.
Service defects are not always easy to measure because service output is not usually a trangible, physical item.
Service organizations and manufacturing companies both convert inputs into outputs—products or services—through a productive process. Both manufacturing and services use the same kinds of inputs—resources such as physical facilities, capital, materials, equipment, and people. In some instances the processes and products are similar. For example, both Toyota and McDonald's produce a tangible, physical product (cars and hamburgers) assembled from component parts. However, in pure service industries such as law, hotels, entertainment, communication, engineering, education, clubs, real estate, banks, retail, health care, and airlines, the processes are less similar and the products are not as tangible. The “products” provided by these organizations are not typically a physical item that can be held or stored. The customer of a manufacturer tends to interact only at the output end of the production process. The customer of a service often interacts directly with the production process, consuming services like legal advice, a classroom lecture, or an airline flight as they are being produced. Services tend to be customized and provided at the convenience of the customer: for example, doctors prescribe individually to patients. In addition, services tend to be labor intensive, while manufacturing is more capital-intensive. Thus, human contact and its ramifications are an important part of the process of producing services.
Services tend to be labor intensive.
If a manufactured item is defective, the defect can usually be felt or seen, and counted or measured. The improvement (or deterioration) in a product's quality can likewise be measured. It's not the same for service. A service cannot be held, felt, stored, and used again. A service output is not always tangible; thus, it is not as easy to measure service defects. The dimensions of service quality include timeliness, courtesy, consistency, accuracy, convenience, responsiveness, and completeness—all hard to measure beyond a subjective assessment by the customer. This does not mean that the potential for quality improvement is any less in services. Each day thousands of travelers check into and out of Ritz-Carlton Hotels, UPS handles and delivers millions of packages, and VISA processes millions of credit transactions worldwide. However, it is sometimes more difficult to assess defects in service and thus more difficult to measure customer satisfaction.
Disney World, for example, has had to develop a “different” view of quality than a manufacturing company. In some ways, a theme park is similar to an assembly line except that Disney's rides have to work flawlessly all the time. However, the Disney experience is not just about defect-free rides. It is also about customer emotions and expectations, which are likely to vary widely. Customers have different tolerance levels for things that go wrong. When there is a long line at a ride, the issue is not just the length of the wait, but how a customer feels about waiting. Disney addresses this problem by being innovative: costumed characters entertain customers waiting in line.
Services and manufacturing companies have similar inputs but different processes and outputs.
QUALITY ATTRIBUTES IN SERVICES
Timeliness is an important dimension of service quality.
Professional football player Drew Brees and wife Brittany check in as the first guests of the Ritz-Cartton in New Orleans when it reopened after Hurricane Katrina. The Ritz-Carlton is the only two-time winner of the Malcolm Baldrige National Quality Award in the service category and its goal is a totally defect-free experience for its guests.
Timeliness, or how quickly a service is provided, is an important dimension of service quality, and it is not difficult to measure. The difficulty is determining what is “quick” service and what is “slow” service. How long must a caller wait to place a phone catalogue order before it is considered poor service? The answer, to a large extent, depends on the caller's expectations: “too long” is not the same for everyone. Varying expectations make it difficult to determine an exact specification.
Quality management in services must focus also on employee performance related to intangible, difficult-to-measure quality dimensions. The most important quality dimensions may be how correctly and pleasantly employees are able to provide service. That is why service companies such as Federal Express, Starbuck's, Avis, Disney, and Ritz-Carlton Hotels have well-developed quality management programs that focus on employee performance, behavior, and training, and serve as “ benchmarks ” for other companies. Service companies lose more customers because either their service is poor or their competitor's is better, than for any other reason, including price.
The principles of TQM apply equally well to services and manufacturing.
Benchmark:
“best” level of quality achievement in one company that other companies seek to achieve.
McDonald's has a reputation for high-quality service resulting from its application of established quality management principles. It provides fresh food promptly on demand. Restaurant managers meet with customer groups on a regular basis and use questionnaires to identify quality “defects” in its operation. It monitors all phases of its process continuously from purchasing to re-strooms to restaurant decor and maintenance. It empowers all employees to make spot decisions to dispose of unfresh food or to speed service. The McDonald's workforce is flexible so that changes in customer traffic and demand can be met promptly by moving employees to different tasks. Food is sampled regularly for taste and freshness. Extensive use is made of information technology for scheduling, cash register operation, food inventory, cooking procedures, and food assembly processes—all with the objective of faster service. All of these quality improvement procedures are standard and similar to approaches to quality improvement that could be found in a manufacturing firm.
ALONG THE SUPPLY CHAIN Ritz-Carlton Hotels: Two-Time Baldrige National Quality Award Winner
The Ritz-Carlton Hotel Company is the only two-time recipient of the Malcolm Baldrige National Quality Award in the service category, having won in 1992 and 1999. An independently operated division of Marriott International, Inc., it manages luxury hotels around the world. All have received four- or five-star ratings from the Mobil Travel Guide and diamond ratings from the American Automobile Association.
The goal for customer satisfaction is a defect-free experience for guests and 100% customer loyalty. The hotel employs a measurement system to chart progress toward elimination of customer problems, no matter how minor. To meet its goal of total elimination of problems, the Ritz-Carlton has identified over 1000 potential instances for a problem to arise during interactions with guests. To cultivate customer loyalty the hotel has instituted an approach of “Customer Customization.” which relies on extensive data gathering. Information gathered during various types of customer contacts, such as responses to service requests by overnight guests or post-event reviews with meeting planners, are systematically entered into a database, which holds almost a million files. The database enables hotel staff worldwide to anticipate the needs of returning guests. The “Greenbook” is the Ritz-Carlton handbook of quality processes and tools, a nearly constant reference that is distributed to all employees. Any employee can spend several thousand dollars to immediately correct a guest's problem or handle a complaint.
More than 85% of the company's 28,000 employees— known as “The Ladies and Gentlemen of the Ritz-Carlton”— are front-line hotel workers. The hotel's “pride and joy” program gives employees a larger role in the design of their jobs. First-year managers and employees receive over 300 hours of training. As a result, the hotel's employee turnover rate, in an industry in which employee turnover is a chronic problem, has declined over a long period, and levels of employee satisfaction are very high.
In an independent customer survey, more than 80% of guests said they were extremely satisfied and 99% said they were satisfied with their overall Ritz-Carlton experience, compared with under 70% for their nearest luxury hotel competitor. Revenue per available room (the industry's measure of market share) has exceeded the industry average by more than 300%.
The Ritz-Carlton is an expensive luxury hotel chain. Do you think this enables it to have an approach to quality that less-expensive, economy-class hotel chains cannot afford? Is revenue a factor in implementing a successful QMS, or is it a result?
Source: National Quality Program at the National Institute of Standards and Technology Web site, http://www.quality.nist.gov.
The “Ladies and Gentlemen of the Ritz-Carlton” are the key factor in Ritz-Carlton's receipt of two Malcolm Baldrige National Quality Awards and the highest guest satisfaction level in the luxury hotel industry.
SIX SIGMA
• Inernet Exercises
Six Sigma was first developed at Motorola, and they and other companies have had a great deal of success with it as reported in the “Along the Supply Chain” box on page 77. A number of companies have credited Six Sigma with billions of dollars in cost savings and increased profits, and these reported successes have led many other large and small companies to adopt all or some of the Six Sigma methodology. As a result Six Sigma is currently one of the most popular quality management systems in the world.
• Inernet Exercises
Basically, Six Sigma is a project-oriented methodology (or system) that provides businesses with the tools and expertise to improve their processes. This increase in performance through a decrease in process variation leads to defect reduction (to near zero) and an increase in product and service quality and increased profits. In its simplest form, Six Sigma is based on Deming's PDCA cycle and Joseph Juran's assertion that “all quality improvement occurs on a project-by-project” basis, with elements of kaizen-type employee involvement. In this section we will provide a more detailed description of the elements and components of Six Sigma. Figure 2.9 illustrates the primary elements of a Six Sigma program.
THE SIX SIGMA GOAL −3.4 DPMO
Six Sigma is a process for developing and delivering virtually perfect products and services. The word “sigma” is a familiar statistical term for the standard deviation, a measure of variability around the mean of a normal distribution. In Six Sigma it is a measure of how much a given product or process deviates from perfection, or zero defects. The main idea behind Six Sigma is that if the number of “defects” in a process can be measured, then it can be systematically determined how to eliminate them and get as close to zero defects as possible. In Six Sigma “as close to zero defects as possible” translates into a statistically based numerical goal of 3.4 defects per million opportunities (DPMO), which is the near elimination of defects from a process, product, or service. This is a goal far beyond the quality level at which most companies have traditionally operated. Through the reduction of variation in all processes (i.e., achieving the Six Sigma goal), the overall performance of the company will be improved and significant overall cost savings will be realized.
Six Sigma:
measure of how much a process deviates from perfection.
Figure 2.9 Six Sigma
• Inernet Exercises
ALONG THE SUPPLY CHAIN Motorola's Six Sigma Quality
Motorola began in the late 1920s as a small manufacturer of car radios (hence the name Motorola). It has grown to a $30 billion corporation with more than 68,000 employees at 320 facilities in 73 countries around the world, manufacturing such products as semiconductors, integrated circuits, paging systems, cellular telephones, computers, and wireless communications systems. Motorola was an engineering-oriented company that focused on product development to create new markets. In the mid-1970s it changed its focus from products to customers, with an objective of total customer satisfaction. Motorola is now recognized as having one of the best quality management systems in the world. In 1988 it was among the first group of winners of the prestigious Malcolm Baldrige National Quality Award and in 2002 it was one of very few companies to win the Baldrige Award a second time.
In 1986 it invented Six Sigma and in 1987 Motorola announced its goal of “Six Sigma” quality. This goal effectively changed the focus of quality in the United States, where quality levels had traditionally been measured in terms of percentages or parts per hundred. Motorola's Six Sigma has since become a benchmark standard that many other companies have adopted. Six Sigma has evolved from a metric (or standard) achieved through the application of various methodologies into a complete quality management system (QMS). GE, Ford, Coors, Boeing, Xerox, Bank of America, Honey-well, Kraft Foods, Intel, Microsoft, NASA, Dannon, UPS, Sony, and Texaco are just a few of the companies that have adopted Six Sigma as their quality management system, Motorola has reported over $17 billion in savings with Six Sigma. The companies that have adopted Six Sigma see it as the basis for a “best-in-class” philosophy and a long-term business strategy to achieve overall business improvement. The fundamental objective of Six Sigma is to focus on improvement in key processes and transactions within a company. In this way, waste and cost are driven out as quality and processes improve, and customer satisfaction and loyalty, and thus profits, are increased through continuous business improvement.
All of the companies cited above are large, well-known, national, or international firms. What do you think some of the obstacles might be for a smaller company to implement a Six Sigma program? Are certain features and components of Six Sigma more applicable than others to a small company?
Source: Motorola Web site, http:www.motorola.com.
THE SIX SIGMA PROCESS
As implemented by Motorola, Six Sigma follows four basic steps—align, mobilize, accelerate, and govern. In the first step, “align,” senior executives create a balanced scorecard (see Chapter 1) of strategic goals, metrics and initiatives to identify the areas of improvement that will have the greatest impact on the company's bottom line. Process owners (i.e, the senior executives who supervise the processes) “champion” the creation of high-impact improvement projects that will achieve the strategic goals.
In the second step, “mobilize,” project teams are formed and empowered to act. The process owners select “black belts” to lead well-defined improvement projects. The teams follow a step-by-step, problem-solving approach referred to as DMAIC.
In the third step, “accelerate,” improvement teams made up of black belt and green belt team members with appropriate expertise use an action-learning approach to build their capability and execute the project. This approach combines training and education with project work and coaching. Ongoing reviews with project champions ensure that projects progress according to an aggressive timeline.
In the final step, “govern,” executive process owners monitor and review the status of improvement projects to make sure the system is functioning as expected. Leaders share the knowledge gained from the improvement projects with other parts of the organization to maximize benefit.
In the next few sections we describe some components of the Six Sigma process in greater detail.
Six Sigma process:
the four basic steps of Six Sigma—align, mobilize, accelerate and govern.
ALONG THE SUPPLY CHAIN Six Sigma Highlights
• A Six Sigma team at North Carolina Baptist Hospital reduced the time for getting heart attack patients from the emergency room into the cardiac catheterization lab for treatment by an average of 41 minutes.
• CIGNA Dental insurance company reduced the volume of pending claims by 50% through Six Sigma projects for cycle time reductions and outstanding premiums reductions.
• A Bechtel project team working on the Channel Tunnel Rail Link in the United Kingdom used Six Sigma to save hundreds of hours on different tunneling jobs.
• A Six Sigma project for truck modification at Volvo's North American Truck Division resulted in cost savings of over $1 million; other projects improved forecasting processes and reduced fuel tank replacement down time.
• A Six Sigma team at Ford fixed a body-side molding problem and the resulting process improvements saved $100,000 annually in waste elimination and eliminated customer complaints about the body-side molding lifting off of the car.
• A Six Sigma project at HSBC Securities (USA) to improve the bottom line performance of its U.S. futures business increased net income from $1.9 million to $7.1 million, a 274% increase, with a 10% reduction in staff.
• A Six Sigma project at the Nebraska Medical Center in Omaha successfully reversed a decline in the patient volume in its interventional radiology department (resulting from dissatisfied referring physicians), reducing complaints from referring clinics to zero and increasing patient volume in one year by 21%, and increasing revenues.
• Since implementing Six Sigma in 1999, Ford experienced a 27% decrease in warranty spending in a two-year period and credits Six Sigma with savings of over $2 billion.
• Royal Mail, one of the United Kingdom's largest employers with over 196,000 employees, used Six Sigma for one project to centralize a key process and halved the process workforce from 450 to 220.
• Since implementing Six Sigma on a corporate-wide basis in 1997, Citibank has seen five- and ten-time defect reductions; examples include decreased response times for credit card applications and fewer errors in customer statements.
• Houston's Memorial Hermann Hospital used Six Sigma to increase its reimbursement percentage from Medicare services resulting in savings of $62 million, an almost 50% improvement.
• A Six Sigma probject at Sharp HealthCare facilities in San Diego led to a program to manage blood sugar levels among all of its impatient and intensive care patients, thus avoiding negative outomes in diabetics.
• Six Sigma projects at Bank of America saved the company in excess of $2 billion in 2005 and over $1 billion in 2009; the company completes thousands of Six Sigma projects each year.
IMPROVEMENT PROJECTS
The first step in the Six Sigma process is the identification of improvement projects. These projects are selected according to business objectives and the goals of the company. As such, they normally have a significant financial impact. These projects are not one-time, unique activities as projects are typically thought of, but team-based activities directed at the continuing improvement of a process.
Once projects are identified, they are assigned a champion from upper management who is responsible for project success, providing resources and overcoming organizational barriers. Champions are typically paid a bonus tied to the successful achievement of Six Sigma goals.
Champion:
an executive responsible for project success.
THE BREAKTHROUGH STRATEGY: DMAIC
At the heart of Six Sigma is the breakthrough strategy, a five-step process applied to improvement projects. The five steps in the breakthrough strategy are very similar to Deming's four-stage PDCA cycle (Figure 2.2), although more specific and detailed. The breakthrough strategy steps are define, measure, analyze, improve, and control, (DMAIC) shown in Figure 2.9.
Breakthrough strategy:
define, measure, analyze, improve, control.
Define: The problem is defined, including who the customers are and what they want, to determine what needs to improve. It is important to know which quality attributes are most important to the customer, what the defects are, and what the improved process can deliver.
Measure: The process is measured, data are collected, and compared to the desired state.
Analyze: The data are analyzed in order to determine the cause of the problem.
Improve: The team brainstorms to develop solutions to problems: changes are made to the process, and the results are measured to see if the problems have been eliminated. If not, more changes may be necessary.
Control: If the process is operating at the desired level of performance, it is monitored to make sure the improvement is sustained and no unexpected and undesirable changes occur.
ALONG THE SUPPLY CHAIN North Shore University Hospital: A Six Sigma Project Example
North Shore University Hospital in Manhasset, New York is part of the North Shore-Long Island Jewish Health System, the third largest nonsectarian health system in the United States with 14 hospitals. The hospital used Six Sigma on a project to reduce delays in bed assignment turnaround time. The problem analysis showed that delays in the post-anesthesia care unit and the emergency department resulted in the hospital not always having the staff or beds available to accept additional patients, which resulted in delays in start times in the operating room and a decrease in patient and physician satisfaction. It was subsequently realized that staff were incorrectly using the bed tracking system (BTS), the electronic system that indicates the status of each bed. Delays in bed turnaround time resulted in delayed notification of a ready bed to the RN (registered nurse) responsible for the patient admission process. This led to delays in the operating room and emergency department and impacted the patient flow throughout the hospital. The bed turnaround time was from the time discharge instructions were given to a patient to the time the admission RN was made aware of a ready bed, a process involving many people. The project focused on one surgical nursing unit which had 2,578 discharged patients in one year.
During the “define” stage of the Six Sigma DMAIC process the project team developed a process map that described in detail the steps of the discharge-admission process. The admissions RNs were identified as the primary customers of the process and they were surveyed to establish process targets. These “voice of the customer (VoC)” responses helped establish a target turnaround time of 120 minutes with an upper limit of 150 minutes. In the “measure” stage of DMAIC a defect was defined as anytime the turnaround time exceeded 150 minutes. The team measured the process by having a team member on the surgical unit monitor the process for one week, which yielded data on 195 patients. Based on this data (which showed 130 defects) the team calculated a DPMO of 672,725, which translated to a score of 1 sigma. The average turnaround time was 226 minutes. The team then developed a cause and effect diagram to help identify all the variables that affected the turnaround time.
During the “analyze” step of the DMAIC process the variables that impacted the turnaround time process (Xs) were discussed, targeted for statistical analysis, and prioritized. A statistical t-test. for example, showed there was no statistical difference in the process based on the day of the week or shift. The team investigations at this stage showed both a communication failure and a technical failure at two key steps in the process that caused significant delays. The team realized that the staff lacked proficiency in the use of the BTS. The lack of communication between the admission RNs and other patient care team members was identified as a priority, as was the lack of timely notification of a ready bed to the admission RN. Several solutions were developed to resolve these problems, including staff training and the use of improved documentation about discharge patients, laminated bedside cards, and reformatted beepers for RNs to accelerate the process. In the “improve” step, the turnaround time was reduced from a mean of 226 minutes to 90 minutes, which resulted in a metric of 2.3 sigma by the time the project ended. In the “control” step moving range and SPC charts were used to monitor turnaround times, and the turnaround time continued to improve to 69 minutes.
The results of this project were subsequently applied to all nursing units in the hospital. Patient satisfaction scores improved in two categories related to readiness for discharge and speed of the discharge process. Since initiating their Six Sigma program the health system has completed over 60 Six Sigma projects and trained 24 black belts, 70 green belts and two master black belts.
Identify a process in a hospital, restaurant, school, or other service that you think might be improved by the Six Sigma DMAIC process, and discuss how you would apply it, including the specific DMAIC stages.
Source: A. Pellicone and M. Martocci, “Faster Turnaround Time,” Quality Progress 39 (3: March 2006), pp. 31-36.
BLACK BELTS AND GREEN BELTS
The project leader who implements the DMAIC steps is called a Black Belt . Black Belts hold full-time positions and are extensively trained in the use of statistics and quality-control tools, as well as project and team management. A Black Belt assignment normally lasts two years during which the Black Belt will lead 8 to 12 projects from different areas in the company, each lasting about one quarter. A Black Belt is certified after two successful projects. Black Belts are typically very focused change agents who are on the fast track to company advancement, Figure 2.10 describes some of the most important tools used by black belts at Motorola.
Black Belt:
the project leader.
Master Black Belts monitor, review, and mentor Black Belts across all projects. They are primarily teachers who are selected based on their quantitative skills, and on their teaching and mentoring ability. As such, they are a resource for project teams and Black Belts. They also hold full-time positions and are usually certified after participating in about 20 successful projects, half while a Black Belt and half as a Master Black Belt.
Master Black Belt:
a teacher and mentor for Black Belts.
Project team members are Green Belts , which is not a full-time position; they do not spend all of their time on projects. Green Belts receive similar training as Black Belts but somewhat less of it.
Green Belts:
project team members.
At General Electric employees are not considered for promotion to any management position without Black Belt or Green Belt training. It is part of the Six Sigma overall strategy that as Black Belts and Green Belts move into management positions they will continue to promote and advance Six Sigma in the company. A generally held perception is that companies that have successfully implemented Six Sigma have one Black Belt for every 100 employees and one Master Black Belt for every 100 Black Belts. This will vary according to the size of the company and the number of projects regularly undertaken. At GE, black belt projects typically save $250,000 or more and green belt projects frequently yield savings in the $50,000 to $75,000 range.
In Six Sigma all employees receive training in the Six Sigma breakthrough strategy, statistical tools, and quality-improvement techniques. Employees are trained to participate on Six Sigma project teams. Because quality is considered to be the responsibility of every employee, every employee must be involved in, motivated by. and knowledgeable about Six Sigma.
DESIGN FOR SIX SIGMA
An important element of the Six Sigma system is Design for Six Sigma (DFSS) , a systematic methodology for designing products and processes that meet customer expectations and can be produced at Six Sigma quality levels. It follows the same basic approach as the breakthrough strategy with Master Black Belts, Black Belts, and Green Belts and makes extensive use of statistical tools and design techniques, training, and measurement. However, it employs this strategy earlier, up front in the design phase and developmental stages. This is a more effective and less expensive way to achieve the Six Sigma goal than fixing problems after the product or process is already developed and in place.
Design for Six Sigma (DFSS):
a systematic approach to designing products and processes that will achieve Six Sigma.
LEAN SIX SIGMA
A recent trend in quality management is Lean Six Sigma (also known as Lean Sigma), that integrates Six Sigma and “lean systems.” Lean systemsns the subject of Chapter 16 so we do not offer a detailed presentation of it at this point; rather we will discuss lean systems in general terms and how it relates to Six Sigma.
Lean Six Sigma:
integrating Six Sigma and lean systems.
Figure 2.10 Six Sigma Tools
Lean is a systematic method for reducing the complexity of a process and making it more efficient by identifying and eliminating sources of waste in a process (such as materials, labor, and time) that hinder flow. Lean basically seeks to optimize process flows through the organization in order to create more value for the customer with less work; i.e., get the product through the process faster. The lean process management philosophy was derived mainly from the Toyota Production System (including push and pull production, JIT and kanbans; see Chapter 16) that has been very effective in manufacturing. As in the case of TPS. lean is basically a more sophisticated extension of earlier efforts to achieve efficiency (i.e., speed) in a manufacturing process by OM pioneers like Henry Ford and Frederick R Taylor.
The lean approach to process improvement includes five steps. First it is determined what creates value for the customer, i.e., quality from the customer's perspective discussed earlier in this chapter. Second, the sequence of activities (in the process) that create value, called the “value stream.” is identified, and those activities that do not add value are eliminated from the production process. Third, waste (such as inventory or long process times) along the value stream is removed through process improvements. Fourth, the process is made responsive to the customer's needs: i.e., making the product or service available when the customer needs it. Finally, lean continually repeats the attempt to remove waste (non-value activity) and improve flow; it seeks perfection. As such, lean is more of a philosophical approach to continuous improvement by eliminating waste throughout the organization everywhere along the value stream by involving everyone in the organization.
Lean Six Sigma attempts to combine the best features of lean and Six Sigma. As we have discussed. Six Sigma is a disciplined and very organized approach for improving processes and preventing defects. It employs a specific program (DMAIC) to identify and eliminate waste and achieve perfection (no defects). By focusing on reducing and controlling variation in targeted processes in an organization (via projects), Six Sigma improves the organization's performance. Through process improvement methods lean attempts to eliminate waste and accelerate process efficiency and flow times, thus increasing value to the customer. Lean improvements cause products to flow through processes faster while Six Sigma improves quality and prevents defects by reducing variation through individual projects. Six Sigma identifies the key factors in the performance of a process and sets them at their best level. Lean reduces the complexity of processes everywhere by eliminating waste that can slow down process flow. Lean focuses on what should not be done in a process and removes it; Six Sigma considers what should be done and how to get it right for all time.
The common link between the two is that they both seek to improve processes and provide value to the customer; however they go about it in different ways. The proponents of Lean Six Sigma believe the two approaches complement each other, and that combining them can result in greater benefits than implementing them separately. However, others consider lean and Six Sigma to be mostly incompatible; Six Sigma is considered to be more of a management tool (i.e., a program), whereas lean is a philosophical approach to process improvement that, like the Toyota Production System, is most effective in a mass manufacturing setting.
THE BOTTOM LINE—PROFITABILITY
The criterion for selecting Six Sigma projects by executives is typically based on the financial impact of the improvement expected from the project—how it will affect the bottom line. This focus on profitability for initiating quality improvement projects is one of the factors that distinguishes Six Sigma from TQM.
In Quality Is Free, Philip Crosby states that, “Quality is not only free, it is an honest-to-every-thing profit maker.” Gary L. Tooker, former CEO and vice chairman of Motorola, in response to the question, “Is there a link between quality and profitability?” responded that “We've saved several billion dollars over the last year because of our focus on quality improvement and the Six Sigma initiative …. there is no doubt about the fact that it has enhanced our bottom line.”
This is only the tip of a mountain of conclusive evidence that quality improvement and profitability are closely related. As quality improves, the costs associated with poor quality decline. Quality improvements result in increased productivity. As the quality of a company's products or services improve, it becomes more competitive and its market share increases. Customers' perception of a company's products as being of high quality and its competitive posture enables the company to charge higher prices. Taken together, these things result in higher profitability.
Example 2.1 describes a scenario that illustrates that impact of profitability that can result from a Six Sigma project.
Example 2.1 The Impact of Six Sigma on Profit
The Medtek Company produces parts for an electronic bed tracking system (BTS) it sells to medical suppliers and hospitals. It contracted for and sold 1,000 units of one of its products during the past quarter for $1,000 each resulting in total sales of $1,000,000. During the quarter the company incurred variable costs (e.g., direct labor, materials and energy) of $600,000, thus the unit variable cost was $600. The company also incurred fixed costs of $350,000 (for items such as plant and equipment, and management salaries) during the quarter. This resulted in a (before-tax) profit of $50,000, as shown in the following income statement:
Sales
$1,000,000
Variable costs
600,000
Fixed costs
350,000
Profit
$50,000
However, now let's consider another factor—the company currently operates with a 10% defects rate and the defective products cannot be reworked. Since the company sold 1,000 products it actually had to produce 1,111 units (i.e., 1,000/0.90 = 1,111), or 111 extra units to compensate for the scrapped units. The variable cost includes this cost of making scrap so the unit variable cost is really $540.05 (i.e., $600,000/1,111 = $540.05). The company has paid a “quality tax” (sometimes called the “hidden factory”) of $59,946 (i.e., 111 scrap units × $540.05 per unit = $59,946).
Now let's assume that the company implements a successful Six Sigma improvement project and it achieves a defect level of 3.4 DPMO, or virtually zero defects. The elimination of defects will (at a minimum) erase the variable costs consumed by making those 111 scrap units. The effect of the elimination of this “quality tax” is shown in the following revised income statement:
Sales
$1,000,000
Variable costs
540,054
Fixed costs
350,000
Profit
$109,946
The company's profit has more than doubled! An approximate 10% reduction in variable costs because of Six Sigma has resulted in a 120% increase in profit. And, the company has actually increased its capacity to 1,111 units without spending more on plant and equipment.
Next assume that the company spent, $120,000 on the Six Sigma project to eliminate defects. If the project was completed in one quarter and the company expects to benefit from the project for 3 years, or 12 quarters, the company should add $10,000 to fixed costs on its income statement:
Sales
$1,000,000
Variable costs
540,054
Fixed costs
360,000
Profit
$99,946
The increase in profit is $49,946 (i.e., $99,946 − 50,000 = $49,946), which is still almost double the profit before Six Sigma. Ignoring interest rates this represents about a 33% return on the company's investment in the Six Sigma project:
Source: S. Bisgaard and J. Freiesleben, “Six Sigma and the Bottom Line,” Quality Progress 39 (9: September 2004), pp. 57-62.
THE COST OF QUALITY
According to legendary quality guru Armand Feigenbaum, “quality costs are the foundation for quality systems economics.” Quality costs have traditionally served as the basis for evaluating investments in quality programs. The costs of quality are those incurred to achieve good quality and to satisfy the customer, as well as costs incurred when quality fails to satisfy the customer. Thus, quality costs fall into two categories: the cost of achieving good quality, also known as the cost of quality assurance, and the cost associated with poor-quality products, also referred to as the cost of not conforming to specifications.
Two recent trends are driving a renewed interest within organizations for measuring quality costs. First, the most recent version of ISO 9000 emphasizes measurements and requires that quality improvement be quantifiably demonstrated. Maintaining quality cost data can provide ISO auditors with evidence of improvement in an organization applying for ISO certification. Second, the popularity and proliferation of Six Sigma, which emphasizes the financial impact of projects as a measure of improvement, has created a need in organizations for quality cost data in order to determine project success.
THE COST OF ACHIEVING GOOD QUALITY
The costs of a quality management program are prevention costs and appraisal costs. Prevention costs are the costs of trying to prevent poor-quality products from reaching the customer. Prevention reflects the quality philosophy of “do it right the first time,” the goal of a quality management program. Examples of prevention costs include:
Prevention costs:
costs incurred during product design.
Quality planning costs: The costs of developing and implementing the quality management program.
Product-design costs: The costs of designing products with quality characteristics.
Process costs: The costs expended to make sure the productive process conforms to quality specifications.
Training costs: The costs of developing and putting on quality training programs for employees and management.
Information costs: The costs of acquiring and maintaining (typically on computers) data related to quality, and the development and analysis of reports on quality performance.
The costs of preventing poor quality include planning, design, process, training, and information costs.
Appraisal costs are the costs of measuring, testing, and analyzing materials, parts, products, and the productive process to ensure that product-quality specifications are being met. Examples of appraisal costs include:
Appraisal costs:
costs of measuring, testing, and analyzing.
Inspection and testing: The costs of testing and inspecting materials, parts, and the product at various stages and at the end of the process.
Test equipment costs: The costs of maintaining equipment used in testing the quality characteristics of products.
Operator costs: The costs of the time spent by operators to gather data for testing product quality, to make equipment adjustments to maintain quality, and to stop work to assess quality.
Costs of measuring quality include inspection, testing, equipment, and operator costs.
Appraisal costs tend to be higher in a service organization than in a manufacturing company and, therefore, are a greater proportion of total quality costs. Quality in services is related primarily to the interaction between an employee and a customer, which makes the cost of appraising quality more difficult. Quality appraisal in a manufacturing operation can take place almost exclusively in-house; appraisal of service quality usually requires customer interviews, surveys, questionnaires, and the like.
THE COST OF POOR QUALITY
The cost of poor quality (COPQ) is the difference between what it actually costs to produce a product or deliver a service and what it would cost if there were no defects. Most companies find that defects, rework and other unnecessary activities related to quality problems significantly inflate costs; estimates range as high as 20 to 30% of total revenues. This is generally the largest quality cost category in a company, frequently accounting for 70 to 90% of total quality costs. This is also where the greatest cost improvement is possible.
The cost of poor quality can be categorized as internal failure costs or external failure costs. Internal failure costs are incurred when poor-quality products are discovered before they are delivered to the customer. Examples of internal failure costs include:
Internal failure costs:
include scrap, rework, process failure, downtime, and price reductions.
Scrap costs: The costs of poor-quality products that must be discarded, including labor, material, and indirect costs.
Rework costs: The costs of fixing defective products to conform to quality specifications.
Process failure costs: The costs of determining why the production process is producing poor-quality products.
Process downtime costs: The costs of shutting down the productive process to fix the problem.
Price-downgrading costs: The costs of discounting poor-quality products—that is, selling products as “seconds.”
External failure costs are incurred after the customer has received a poor-quality product and are primarily related to customer service. Examples of external failure costs include:
External failure costs:
include comptaints, returns, warranty claims, liability, and lost sales.
Customer complaint costs: The costs of investigating and satisfactorily responding to a customer complaint resulting from a poor-quality product.
Product return costs: The costs of handling and replacing poor-quality products returned by the customer. In the United States it is estimated that product returns reduce company profitability by an average of 4% annually.
Warranty claims costs: The costs of complying with product warranties.
Product liability costs: The litigation costs resulting from product liability and customer injury.
Lost sales costs: The costs incurred because customers are dissatisfied with poor-quality products and do not make additional purchases.
Internal failure costs tend to be low for a service, whereas external failure costs can be quite high. A service organization has little opportunity to examine and correct a defective internal process, usually an employee-customer interaction, before it actually happens. At that point it becomes an external failure. External failures typically result in an increase in service time or inconvenience for the customer. Examples of external failures include a customer waiting too long to place a catalogue phone order; a catalogue order that arrives with the wrong item, requiring the customer to repackage and send it back; an error in a charge card billing statement, requiring the customer to make phone calls or write letters to correct it; sending a customer's orders or statements to the wrong address; or an overnight mail package that does not arrive overnight.
MEASURING AND REPORTING QUALITY COSTS
Collecting data on quality costs can be difficult. The costs of lost sales, of responding to customer complaints, of process downtime, of operator testing, of quality information, and of quality planning and product design are all costs that may be difficult to measure. These costs must be estimated by management. Training costs, inspection and testing costs, scrap costs, the cost of product downgrading, product return costs, warranty claims, and liability costs can usually be measured. Many of these costs are collected as part of normal accounting procedures.
Management wants quality costs reported in a manner that can be easily interpreted and is meaningful. One format for reporting quality costs is with index numbers , or indices. Index numbers are ratios that measure quality costs relative to some base value, such as the ratio of quality costs to total sales revenue or the ratio of quality costs to units of final product. These index numbers are used to compare quality management efforts between time periods or between departments or functions. Index numbers themselves do not provide very much information about the effectiveness of a quality management program. They usually will not show directly that a company is producing good- or poor-quality products. These measures are informative only when they are compared to some standard or other index. Some common index measures are:
Index numbers:
ratios that measure quality costs against a base value.
Labor index: The ratio of quality cost to direct labor hours; it has the advantage of being easily computed (from accounting records) and easily understood, but it is not always effective for long-term comparative analysis when technological advances reduce labor usage.
Cost index: The ratio of quality cost to manufacturing cost (direct and indirect cost); it is easy to compute from accounting records and is not affected by technological change.
Sales index: The ratio of quality cost to sales; it is easily computed, but it can be distorted by changes in selling price and costs.
Production index: The ratio of quality cost to units of final product; it is easy to compute from accounting records but is not effective if a number of different products exist.
Labor index:
the ratio of quality cost to labor hours.
Cost index:
the ratio of quality cost to manufacturing cost.
Sales index:
the ratio of quality cost to sales.
Production index:
the ratio of quality cost to units of final product.
Example 2.2 illustrates several of these index numbers.
Example 2.2 An Evaluation of Quality Costs and Quality Index Numbers
The H&S Motor Company produces small motors (e.g., 3 hp) for use in lawnmowers and garden equipment. The company instituted a quality management program in 2006 and has recorded the following quality cost data and accounting measures for four years.
Year
2006
2007
2008
2009
Quality Costs
Prevention
$27,000
41,500
74,600
112,300
Appraisal
155,000
122,500
113,400
107,000
Internal failure
386,400
469,200
347,800
219,100
External failure
242,000
196,000
103,500
106,000
Total
$810,400
829,200
639,300
544,400
Accounting Measures
Sales
$4,360,000
4,450,000
5,050,000
5,190,000
Manufacturing costs
1,760,000
1,810,000
1,880,000
1,890,000
The company wants to assess its quality management program and develop quality index numbers using sales and manufacturing cost bases for the four-year period.
Solution
The H&S Company experienced many of the typical outcomes when its quality management program was instituted. Approximately 78% of H&S's total quality costs are a result of internal and external failures, not unlike many companies. Failure costs frequently contribute 50 to 90% of overall quality costs. The typical reaction to high failure costs is to increase product monitoring and inspection to eliminate poor-quality products, resulting in high appraisal costs. This appeared to be the strategy employed by H&S when its quality management program was initiated in 2006. In 2007, H&S was able to identify more defective items, resulting in an apparent increase in internal failure costs and lower external failure costs (as fewer defective products reached the customer).
During 2006 and 2007, prevention costs were modest. However, prevention is critical in reducing both internal and external failures. By instituting quality training programs, redesigning the production process, and planning how to build in product quality, companies are able to reduce poor-quality products within the production process and prevent them from reaching the customer. This was the case at H&S, because prevention costs increased by more than 300% during the four-year period. Since fewer poor-quality products are being made, less monitoring and inspection is necessary, and appraisal costs thus decline. Internal and external failure costs are also reduced because of a reduction in defective products. In general, an increase in expenditures for prevention will result in a decrease in all other quality-cost categories. It is also not uncommon for a quality management program to isolate one or two specific quality problems that, when prevented, have a large impact on overall quality cost reduction. Quality problems are not usually evenly distributed throughout the product process; a few isolated problems tend to result in the majority of poor-quality products.
The H&S Company also desired to develop index numbers using quality costs as a proportion of sales and manufacturing costs, generally two of the more popular quality indexes. The general formula for these index numbers is
For example, the index number for 2006 sales is
The quality index numbers for sales and manufacturing costs for the four-year period are given in the following table.
Year
Quality Sales Index
Quality Manufacturing Cost Index
2006
18.58
46.04
2007
18.63
45.18
2008
12.66
34.00
2009
10.49
28.80
These index numbers alone provide little insight into the effectiveness of the quality management program; however, as a standard to make comparisons over time they can be useful. The H&S Company quality index numbers reflect dramatically improved quality during the four-year period. Quality costs as a proportion of both sales and manufacturing costs improved significantly. Quality index numbers do not provide information that will enable the company to diagnose and correct quality problems in the production process. They are useful in showing trends in product quality over time and reflecting the impact of product quality relative to accounting measures with which managers are usually familiar.
THE QUALITY-COST RELATIONSHIP
In Example 2.2 we showed that when the sum of prevention and appraisal costs increased, internal and external failure costs decreased. Recall that prevention and appraisal costs are the costs of achieving good quality, and internal and external failure costs are the costs of poor quality. In general, when the cost of achieving good quality increases, the cost of poor quality declines.
Philip Crosby's fourth absolute from his 1984 book Quality Without Tears, explains that the dollar cost of quality is the difference between the price of nonconformance, the cost of doing things wrong (i.e., the cost of poor quality), and the price of conformance, the cost of doing things right (i.e., the cost of achieving good quality). He estimates that the cost of doing things wrong can account for 20 to 35% of revenues, while the cost of doing things right is typically 3 to 4%. As such, managers should determine where the cost of quality is occurring and find out what causes it.
The cost of quality is the difference between the price of nonconformance and conformance.
Companies committed to quality improvement know that the increase in sales and market share resulting from increased customer satisfaction offsets the costs of achieving good quality. Furthermore, as a company focuses on good quality, the cost of achieving good quality will be less because of the improvements in technologies and processes that will result from the quality improvement effort. These companies are frequently the ones that seek to achieve zero defects, the goal of Six Sigma.
The Japanese first recognized that the costs of poor quality had been traditionally underestimated. These costs did not take into account the customer losses that can be attributed to a reputation for poor quality. The Japanese viewed the cost associated with a reputation for poor quality to be quite high. A General Accounting Office report on companies that have been Baldrige Quality Award finalists has shown that corporate wide quality improvement programs result in higher worker motivation, improved employee relations, increased productivity, higher customer satisfaction, and increased market share and profitability.
THE EFFECT OF QUALITY MANAGEMENT ON PRODUCTIVITY
In the previous section we saw how an effective quality management program can help to reduce quality-related costs and improve market share and profitability. Quality management can also improve productivity—the number of units produced from available resources.
PRODUCTIVITY
Productivity is a measure of a company's effectiveness in converting inputs into outputs. It is broadly defined as
Productivity:
the ratio of output to input.
An output is the final product from a service or production process, such as an automobile, a hamburger, a sale, or a catalogue order. Inputs are the parts, material, labor, capital, and so on that go into the productive process. Productivity measures, depending on the outputs and inputs used, are labor productivity (output per labor-hour) and machine productivity (output per machine-hour).
Quality impact on productivity:
Fewer defects increase output and quality improvement reduces inputs.
Improving quality by reducing defects will increase good output and reduce inputs. In fact, virtually all aspects of quality improvement have a favorable impact on different measures of productivity. Improving product design and production processes, improving the quality of materials and parts, and improving job designs and work activity will all increase productivity.
MEASURING PRODUCT YIELD AND PRODUCTIVITY
Product yield is a measure of output used as an indicator of productivity. It can be computed for the entire production process (or for one stage in the process) as follows:
Yield:
a measure of productivity.
or
where
I = planned number units of product started in the production process
% G = percentage of good units produced
% R = percentage of defective units that are successfully reworked
Improved quality increases product yield.
In this formula, yield is the sum of the percentage of products started in the process (or at a stage) that will turn out to be good quality plus the percentage of the defective (rejected) products that are reworked. Any increase in the percentage of good products through improved quality will increase product yield.
Example 2.3 Computing Product Yield
The H&S Motor Company starts production for a particular type of motor with a steel motor housing. The production process begins with 100 motors each day. The percentage of good motors produced each day averages 80% and the percentage of poor-quality motors that can be reworked is 50%. The company wants to know the daily product yield and the effect on productivity if the daily percentage of good-quality motors is increased to 90%.
Solution
If product quality is increased to 90% good motors, the yield will be
A 10 percentage-point increase in quality products results in a 5.5% increase in productivity output.
Now we will expand our discussion of productivity to include product manufacturing cost. The manufacturing cost per (good) product is computed by dividing the sum of total direct manufacturing cost and total cost for all reworked units by the yield, as follows:
or
where
Kd = direct manufacturing cost per unit
I = input
Kr = rework cost per unit
R = reworked units
Y = yield
Example 2.4 Computing Product Cost per Unit
The H&S Motor Company has a direct manufacturing cost per unit of $30, and motors that are of inferior quality can be reworked for $12 per unit. From Example 2.3, 100 motors are produced daily, 80% (on average) are of good quality and 20% are defective. Of the defective motors, half can be reworked to yield good-quality products. Through its quality management program, the company has discovered a problem in its production process that, when corrected (at a minimum cost), will increase the good-quality products to 90%. The company wants to assess the impact on the direct cost per unit of improvement in product quality.
Solution
The original manufacturing cost per motor is
The manufacturing cost per motor with the quality improvement is
The improvement in the production process as a result of the quality management program will result in a decrease of $2.46 per unit, or 7.1%, in direct manufacturing cost per unit as well as a 5.5% increase in product yield (computed in Example 2.3), with a minimal investment in labor, plant, or equipment.
In Examples 2.3 and 2.4 we determined productivity measures for a single production process. However, it is more likely that product quality would be monitored throughout the production process at various stages. Each stage would result in a portion of good-quality, “work-in-process” products. For a production process with n stages, the yield, Y (without reworking), is
where
I = input of items to the production process that will result in finished products
gi = good-quality, work-in-process products at stage i
Example 2.5 Computing Product Yield for a Multistage Process
At the H&S Motor Company, motors are produced in a four-stage process. Motors are inspected following each stage, with percentage yields (on average) of good-quality, work-in-process units as follows.
Stage
Average Percentage Good Quality
1
0.93
2
0.95
3
0.97
4
0.92
The company wants to know the daily product yield for product input of 100 units per day. Furthermore, it would like to know how many input units it would have to start with each day to result in a final daily yield of 100 good-quality units.
Solution
Thus, the production process has a daily good-quality product yield of 78.8 motors.
To determine the product input that would be required to achieve a product yield of 100 motors, I is treated as a decision variable when Y equals 100:
To achieve output of 100 good-quality motors, the production process must start with approximately 127 motors.
THE QUALITY-PRODUCTIVITY RATIO
Another measure of the effect of quality on productivity combines the concepts of quality index numbers and product yield. Called the quality-productivity ratio (QPR) ,3 it is computed as follows:
Quality-productivity ratio (QPR):
a productivity index that includes productivity and quality costs.
This is actually a quality index number that includes productivity and quality costs. The QPR increases if either processing cost or rework costs or both decrease. It increases if more good-quality units are produced relative to total product input (i.e., the number of units that begin the production process).
Example 2.6 Computing the Quality Productivity Ratio (QPR)
The H&S Motor Company produces small motors at a processing cost of $30 per unit. Defective motors can be reworked at a cost of $12 each. The company produces 100 motors per day and averages 80% good-quality motors, resulting in 20% defects, 50% of which can be reworked prior to shipping to customers. The company wants to examine the effects of (1) increasing the production rate to 200 motors per day; (2) reducing the processing cost to $26 and the rework cost to $10; (3) increasing, through quality improvement, the product yield of good-quality products to 95%; and (4) the combination of 2 and 3.
Solution
The QPR for the base case is computed as follows.
Case 1. Increase input to production capacity of 200 units.
Increasing production capacity alone has no effect on the QPR; it remains the same as the base case.
Case. 2. Reduce processing cost to $26 and rework cost to $10.
These cost decreases caused the QPR to increase.
Case 3. Increase initial good-quality units to 95 percent.
Again, the QPR increases as product quality improves.
Case 4. Decrease costs and increase initial good-quality units.
The largest increase in the QPR results from decreasing costs and increasing initial good-quality product through improved quality.
3 E. E. Adam, J. E. Hershauer, and W. A. Ruch, Productivity and Quality: Measurement as a Basis of Improvement, 2nd ed. (Columbia, MO: Research Center, College of Business and Public Administration, University of Missouri, 1986).
QUALITY AWARDS
The Baldrige Award, Deming Prize, and other award competitions have become valuable and coveted prizes to U.S. companies eager to benefit from the aura and reputation for quality that awaits the winners, and the decreased costs and increased profits that award participants and winners have experienced. They have also provided widely used sets of guidelines to help companies implement an effective quality management system (QMS), and winners provide quality standards, or “benchmarks,” for other companies to emulate.
THE MALCOLM BALDRIGE AWARD
The Malcolm Baldrige National Quality Award is given annually to one or two companies in each of five categories: manufacturing, services, small businesses (with less than 500 full-time employees), health care, and education. It was created by law in 1987 (named after former Secretary of Commerce Malcolm Baldrige, who died in 1987) to (1) stimulate U.S. companies to improve quality, (2) establish criteria for businesses to use to evaluate their individual quality-improvement efforts, (3) set as examples those companies that were successful in improving quality, and (4) help other U.S. organizations learn how to manage quality by disseminating information about the award winners' programs.
The Baldrige Award was created in 1987 to stimulate growth of quality management in the United States.
The award criteria focus on the soundness of the approach to quality improvement, the overall quality management program as it is implemented throughout the organization, and customer satisfaction. The seven major categories of criteria by which companies are examined are leadership, information and analysis, strategic planning, human resource focus, process management, business results, and customer and market focus.
• Inernet Exercises
The Baldrige Award has had a major influence on U.S. companies, thousands of which request applications from the government each year to obtain a copy of the award guidelines and criteria for internal use in establishing a quality management system. Many companies have made the Baldrige criteria for quality their own, and have also demanded that their suppliers submit applications for the Baldrige Quality Award. Since its inception in 1987, it has been estimated that the economic benefits of the Baldrige award to the U.S. economy is almost $30 billion. Companies that have won the Baldrige Quality Award and have become known as leaders in quality include Motorola, Xerox, Cadillac. Milliken, Federal Express, Ritz Carlton, and IBM. These and other Baldrige Award winners have become models or benchmarks for other companies to emulate in establishing their own quality management systems.
The Malcolm Baldrige National Quality Award is given each year to companies in five categories-manufacturing, services, small businesses, health care and education. The award criteria and guidelines have become a template for a successful quality management system.
Table 2.3 Selected National and International Qaulity Awards
Award
Organization
Description
Malcolm Baldrige Award
National Institute of Standards and Technology
Small business, manufacturing, service, education, and health care
Deming Medal
American Society for Quality
Leader in quality
J.D. Powers Awards
J.D. Powers Associates
Customer satisfaction in a variety of industries
George M. Low Trophy
NASA
NASA suppliers
President's Quality Award
U. S. Office of Personnel Management
Federal government organizations
IIE Award for Excellence in Productivity improvement
Institute of Industrial Engineers
Large and small manufacturing companies and large and small service companies
Distinguished Service Medal
American Society for Quality
Gold medal for individual distinction
International Asia Pacific Award
Asia Pacific Quality Organization
Winners of national quality awards
Australian Business Excellence Awards
Standards Australia International Limited
Excellence medal, gold, silver, and bronze awards open to Australian companies
Canada Awards for Excellence
National Quality Institute
Quality award and healthy workplace award
European Quality Awards
European Foundation for Quality Management (EFQM)
European organizations demonstrating excellence in quality
German National Quality Award
German Society for Quality and Association of German Engineers
EFQM criteria for German companies
Hong Kong Award for Industry
Quality Trade and Industry Dept.
Companies based and operating in Hong Kong
Rajiv Ghandi National Award
Bureau of Indian Standards
Indian manufacturing and service organizations
Japan Quality Award
Japanese Quality Award Committee
Six companies in manufacturing, service, and small/medium businesses
Deming Prize
Union of Japanese Scientists and Engineers
Application prize, individual prize, and quality-control award for business units
Japan Quality Medal
Union of Japanese Scientists and Engineers
Deming application prize companies
Swiss Quality Award
Swiss Association for Promotion of Quality
EFQM criteria for Switzerland
UK Quality Award for Business Excellence
British Quality Foundation
EFQM criteria for United Kingdom
OTHER AWARDS FOR QUALITY
The creation and subsequent success of the Baldrige Award has spawned a proliferation of national, international, government, industry, state, and individual quality awards. Table 2.3 provides information about selected national and international quality awards. (Internet addresses for these awards can be found on the Chapter 2 Web links page on the text Web site.) The American Society for Quality (ASQ) sponsors a number of national individual awards, including, among others, the Armand V. Feigenbaum Medal, the Deming Medal, the E. Jack Lancaster Medal, the Edwards Medal, the Shewart Medal, and the Ishikawa Medal.
The President's Quality Award was established in 1989 to recognize federal government organizations that improve their overall performance and capabilities, demonstrate mature approaches to quality throughout the organization, and demonstrate a sustained trend in high-quality products and services that result in effective use of taxpayer dollars.
Prominent international awards include the European Quality Award, the Canadian Quality Award, the Australian Business Excellence Award, and the Deming Prize from Japan. The countries from which these four awards are administered plus the United States account for approximately 75% of the world's gross national product. The European Quality Award, established in 1991 to recognize outstanding businesses in 16 European countries, is similar in criteria and scope to the Baldrige Award, as are most of the other international awards.
• Inernet Exercises
ALONG THE SUPPLY CHAIN Baldrige National Quality Award Winners: What It Takes
Sunny Fresh Foods in Monticello, Minnesota, is a two-time winner of the Baldrige Award, having won in 1999 and 2005. It provides more than 160 egg-based products to over 2,000 customers including restaurants, business and institutional food services, schools, and the military. It meets 75% of the product needs of four of the country's top users of processed egg products. Since its receipt of its first Baldrige Award in 1999 its revenues have increased 93% and its market share has increased while its competitors' market share has decreased 10. On-time deliveries were at 99.8% in 2005, customer complaints are well below the Six Sigma level, and customer satisfaction remained near 100% from 2001 to 2005.
Sharp HealthCare, a 2007 recipient of the Baldrige Award, is San Diego County's largest health-care delivery system and annually serves more than 27% of the county's 3 million plus residents. In 2001 it began its quality improvement initiative called “The Sharp Experience” with goals of being the best place for employees to work, the best place for physicians to practice, and the best place for patients to receive care. Since then its net revenues have increased by 56% (to almost $2 billion), it has gained more than four percentage points in market share, the heart attack mortality incidence at its three hospitals has been below national benchmarks, San Diego consumers have named Sharp as the region's best health-care provider, in-patient satisfaction with the nursing staff has increased 300%, employee satisfaction has been rated as “best in class” by national standards, and Sharp's employee turnover rate is consistently better than the state benchmark.
Park Place Lexus, a 2005 Baldrige Award winner in Plano and Grapevine, Texas, which sells and services new and pre-owned Lexus vehicles, is the highest rated Lexus dealership in the nation with a New Car Client Satisfaction Index of 99.8%. Customer satisfaction among its pre-owned vehicle clients increased form 96% in 2000 to 98% in 2004, while the company's gross profit percentage increased by 51.3%. Customer satisfaction with the service department approaches 98%. Park Place Lexus uses a “house of quality” to depict its organizational culture with a foundation mission “to provide an extraordinary automotive purchase and ownership experience.”
Iredell-Statesville Schools, a 2008 Baldrige Award recipient, is a K-12 public school system in western North Carolina that serves 21,000 students. Despite having one of the lowest budgets ($160 million) and per student expenditure rates (107 out of 115 school districts) in the state, it consistently outperforms comparative districts at state and national levels across numerous measures. Its average SAT score ranked seventh in the state and exceeded the national averages; it achieved a 91% proficiency score on the state reading assessment, and reduced the gap between African-American children and all students from 23 to 12.3%; it increased high school graduation rates from 61 to 81%; achieved higher attendance rates, lower dropout rates, and lower teacher turnover rates than comparable North Carolina school districts; it increased the number of “highly qualified” teachers from 84 to 97%; and in 2008 was ranked ninth among 115 school districts in North Carolina in student achievement.
Visit the Baldrige Award Web site at www.quality.nist.gov and read more about these and other award recipients, and identify and discuss the common quality-motivated characteristics they share.
Source: National Quality Program at the National Institute of Standards and Technology Web site, http://www.quality.nist.gov.
ISO 9000
• Inernet Exercises
The International Organization for Standardization (ISO), headquartered in Geneva, Switzerland, has as its members the national standards organizations for more than 157 countries. The ISO member for the United States is the American National Standards Institute (ANSI). The purpose of ISO is to facilitate global consensus agreements on international quality standards. It has resulted in a system for certifying suppliers to make sure they meet internationally accepted standards for quality management. It is a nongovernment organization and is not a part of the United Nations.
During the 1970s it was generally acknowledged that the word quality had different meanings within and among industries and countries and around the world. In 1979 the ISO member representing the United Kingdom, the British Standard Institute (BSI), recognizing the need for standardization for quality management and assurance, submitted a formal proposal to ISO to develop international standards for quality assurance techniques and practices. Using standards that already existed in the United Kingdom and Canada as a basis, ISO established generic quality standards, primarily for manufacturing firms, that could be used worldwide.
ISO is not an acronym for the International Organisation for Standardization; it is a word, “ISO,” derived from the Greek “ISO,” meaning “equal.”
ISO 9000 is a set of procedures and policies for the international quality certification of suppliers.
STANDARDS
Standards are documented agreements that include technical specifications or other precise criteria to be used consistently as rules, guidelines, or definitions to ensure that materials, products processes, and services are fit for their purpose. For example, the format for credit cards and phone cards was derived from ISO standards that specify such physical features as the cards' thickness so that they can be used worldwide. Standards, in general, increase the reliability and effectiveness of goods and services used around the world and as a result make life easier for everyone.
The ISO 9000 series of quality management standards, guidelines, and technical reports was first published in 1978, and it is reviewed at least every five years. It was most recently revised and updated in 2008. ISO 9000:2008, Quality Management Systems—Fundamentals and Vocabulary, is the starting point for understanding the standards. It defines the fundamental terms and definitions used in the ISO 9000 family of standards, guidelines, and technical reports. ISO 9001:2008, Quality Management Systems—Requirements, is the requirement standard a company uses to assess its ability to meet customer and applicable regulatory requirements in order to achieve customer satisfaction. ISO 9004:2008, Quality Management Systems—Guidelines for Performance Improvements, provides detailed guidance to a company for the continual improvement of its quality management system in order to achieve and sustain customer satisfaction. The ISO 9000 family includes 10 more published standards and guidelines; however, these three are the most widely used and applicable to the majority of companies.
CERTIFICATION
Many companies around the world require that companies they do business with (e.g., suppliers) have ISO 9001 certification. In that way, despite possible language, technology, and cultural differences, a company can be sure that the company it's doing business with meets uniform standards—that is, they are “on the same page.” ISO 9001:2008 is the only standard in the ISO 9000 family that carries third-party certification (referred to as registration in the United States). A third-party company called a registrar is the only authorized entity that can award ISO 9001 certification. Registrars are accredited by an authoritative national body and are contracted by companies to evaluate their quality management system to see if it meets the ISO 9001 standards; if the company does, it is issued an ISO 9000 certification, which is recognized around the world. The worldwide total of ISO 9001 certifications at the end of 2004 was over 670,000 in 154 countries. This was a 35% increase over the total at the end of 2003.
ISO 9001:2008 primarily serves as a basis for benchmarking a company's quality-management system. Quality management, in ISO terms, measures how effectively management determines the company's overall quality policy, its objectives, and its responsibilities, as well as its quality policy implementation. A company has to fulfill all of the requirements in ISO 9001:2008 to be certified (except for activities and functions it does not perform at all). Customer satisfaction is an explicit requirement. Thus, to be certified a company must identify and review customer requirements, ensure that customer requirements are met, and be able to measure and monitor customer satisfaction. The company must also be able to show that measuring and monitoring customer satisfaction leads to corrective and preventive actions when nonconformance (to the standards) is found—that is, continual improvement. This type of analysis of customer satisfaction requires a large amount of data collection and processing.
IMPLICATIONS OF ISO 9000 FOR U.S. COMPANIES
Originally, ISO 9000 was adopted by the 12 countries of the European Community (EC)—Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, and the United Kingdom. The governments of the EC countries adopted ISO 9000 as a uniform quality standard for cross-border transactions within the EC and for international transactions. The EC has since evolved into the European Union (EU) with 25 member countries.
Thousands of businesses have improved their operations by fully implementing a quality system based on the international standards known as ISO 9001:2008. When a company has met all the requirements of the standards, a registrar will certify/register them. This status is represented by a certificate, such as this sample.
ALONG THE SUPPLY CHAIN ISO 9001 Certification at Monarcas Morelia
Monarcas Morelia (named for the Monarch butterfly) is a professional soccer team in the Mexican Football Federation First Division league, which consists of 19 professional teams. It is the first international-level club soccer team to achieve ISO 9001 certification. The team is owned by TV Azteca, a Spanish language television networks producer, which is owned by Grupo Salinas (GS), a $3.1 billion conglomerate created by Ricardo Salinas. Executives at TV Azteca and Grupo Salinas learned through the ISO certification process at TV Azteca and other GS subsidiaries that a quality management system (QMS) creates value and compels managers to seek continuous improvement and customer satisfaction. In 1998 Monarcas Morelia was at the bottom of the First Division and losing money. The philosophy of Ricardo Salinas was that every GS company must create value, and the football team was no exception. In 1999, eight months after it developed its QMS, Monarcas Morelia began earning a profit, in 2000 it won the Mexican Football Championship for the first time in team history, and in 2002 it finished in second place.
A necessary first step in developing a QMS was for Monarcas Morelia to define its customers, which was determined to be a large, diverse group including fans, investors, employees, visiting teams and their fans, the media, referees, sponsors, charities, and members of its youth development team. Basic Forces, and their families. The quality team led by team president, Alvaro Davila, focused on benchmarking to transform the team's management and seek continual improvement—just as any business would. He visited teams in Argentina, Spain and Germany, and adopted their successful strategies for winning, promoting goodwill and earning profits. He arranged exhibition games and player exchange programs, including a contract with the Chicago Fire of the U.S. MLS. In order to keep the 30,000-seat Morelia. Mexico stadium (including seats, bathrooms, vending outlets and lighting fixtures) in top condition, and continually improve it, the team relied on the steps of the Japanese “gemba kaizen” process (where gemba means “where the action is” and kaizen means “continuous improvement”). The team also established a customer-friendly security system with guards trained to prevent violence and promote a family-friendly atmosphere.
Pick an “entertainment” service like a college or professional athletic team, a theater, an amusement park, etc., and discuss the ways it might benefit from a QMS.
Source: A. Tolumes, “Pitch Perfect,” Qualityworld 32 (1: January 2006), pp. 23-26.
Monarcas Morelia (shown in the yellow jersey with red stripes) went from last place in the Mexican Football Federation First Division league to champions in just two years after developing its QMS based on its ISO 9001 certification process.
Many overseas companies will not do business with a supplier unless it has ISO 9000 certification.
These EU countries and many others are specifically acknowledging that they prefer suppliers with ISO 9000 certification. To remain competitive in international markets. U.S. companies must comply with the standards in the ISO 9000 series. Some products in the EU, for example, are “regulated” to the extent that the products must be certified to be in ISO 9000 compliance by an EU-recognized accreditation registrar. Most of these products have health and safety considerations. However, companies discovered that to remain competitive and satisfy customer preferences, their products had to be in compliance with ISO 9000 requirements even if these products were not specifically regulated.
The United States exports more than $200 billion annually to the EU market, much of it to France, Germany, Italy, Spain, and the United Kingdom. Most of these exports are affected in some way by ISO 9000 standards.
Companies are also pressured within the United States to comply with ISO 9000 by more and more customers. For example, the U.S. Department of Defense, and specifically the Department of the Navy, as well as private companies like DuPont, 3M, and AT&T, adopted ISO 9000. They recognize the value of these standards for helping to ensure top-quality products and services and required that their suppliers comply with ISO 9000.
In the EC registration system, the third-party assessors of quality are referred to as notified bodies; that is, the 12 EC governments notify one another as to which organization in their country is the officially designated government-approved quality assessor. The notified bodies ultimately certify a company with a European Conformity (CE) mark. The CE mark must be on any product exported from the United States that is ISO 9000-regulated. It is illegal to sell a regulated product in a store in the EC without the CE mark. For a supplier in the United States to export regulated products to an EC country, it must be accredited by European registrars—notified bodies within the EC. However, more and more EC companies are requiring ISO 9000 certification for suppliers of products that fall in the unregulated categories, and eventually all products exported to the EC will probably require certification. It is also important that U.S. companies obtain accreditation with a notified body that has widespread positive recognition in the EC so that they will have broad access to markets in the EC.
The U.S. member of the ISO, the American National Standards Institute (ANSI), designated the American Society for Quality (ASQ), as the sponsoring organization for ISO 9000 in the United States. ASQ and ANSI created the Registrar Accreditation Board (RAB) to act as an accrediter of third-party registrars in the United States.
ISO REGISTRARS
A registrar is an organization that conducts audits by individual auditors. Auditors are skilled in quality systems and the manufacturing and service environments in which an audit will be performed. The registrar develops an audit team of one or more auditors to evaluate a company's quality program and then report back to the registrar. An organization that wants to become a registrar must be accredited by RAB. Once RAB accredits a registrar, the registrar can then authorize its registered suppliers to use the RAB certificate in advertising, indicating compliance with ISO 9000.
ISO certification, or registration as it is called in the United States, is accomplished by a registrar through a series of document reviews and facility visits and audits. The registrar's auditors review a company's procedures, processes, and operations to see if the company conforms to the ISO quality management system standards. The registrar looks at a variety of things, including the company's administrative, design, and production processes; quality system documentation; personnel training records; management reviews; and internal audit processes. The registration process might typically include an initial document review that describes the company's quality management system, followed by the development of an audit plan and then the audit itself. This is usually followed by semiannual or annual surveillance audits to make sure the quality system is being maintained. The registration process can take from several weeks up to a year, depending on how ready the company is for registration. A RAB accredited registrar does not “help” the company attain certification either by giving advice or consulting.
SUMMARY
In our discussion of quality management in this chapter, certain consistencies or commonalities have surfaced. The most important perspective of quality is the customer's; products and services must be designed to meet customer expectations and needs for quality. A total commitment to quality is necessary throughout an organization for it to be successful in improving and managing product quality. This commitment must start at the top and filter down through all levels of the organization and across all areas and departments. Employees need to be active participants in the quality-improvement process and must feel a responsibility for quality. Employees must feel free to make suggestions to improve product quality, and a systematic procedure is necessary to involve workers and solicit their input. Improving product quality is cost-effective; the cost of poor quality greatly exceeds the cost of attaining good quality. Quality can be improved with the effective use of statistical quality-control methods. In fact, the use of statistical quality control has been a pervasive part of our discussions on quality management, and it has been identified as an important part of any quality-management program. In the following chapter we concentrate on statistical quality-control methods and principles.
Practice Quizzes
SUMMARY OF KEY FORMULAS
Quality Index Numbers
Product Yield
Manufacturing Cost per Product
Multistage Product Yield
Quality-Productivity Ratio
SUMMARY OF KEY TERMS
appraisal costs
costs of measuring, testing, and analyzing materials, parts, products, and the productive process to make sure they conform to design specifications.
benchmark
a level of quality achievement established by one company that other companies seek to achieve (i.e., a goal).
Black Belt
in a Six Sigma program, the leader of a quality improvement project; a full-time position.
breakthrough strategy
in Six Sigma, a five-step process for improvement projects: define, measure, analyze, improve, and control.
cause-and-effect diagram or fishbone diagram
a graphical description of the elements of a specific quality problem.
cause-and-effect matrix
a grid used to prioritize causes of quality problems.
champion
a member of top management who is responsible for project success in a Six Sigma program.
cost index
the ratio of quality cost to manufacturing cost.
design for Six Sigma (DFSS)
a systematic methodolgy to design products and processes that meet customer expectations and can be produced at Six Sigma quality levels.
external failure costs
costs of poor quality incurred after the product gets to the customer; that is, customer service, lost sales, and so on.
fitness for use
a measure of how well a product or service does what the consumer thinks it is supposed to do and wants it to do.
Green Belt
in a Six Sigma program, a project team member, a part-time position.
index numbers
ratios that measure quality costs relative to some base accounting values such as sales or product units.
internal failure costs
costs of poor-quality products discovered during the production process—that is, scrap, rework, and the like.
kaizen
involving everyone in the workplace, in a process of gradual, organized, and continuous improvement.
labor index
the ratio of quality cost to direct labor hours.
Lean Six Sigma
integrating Six Sigms and lean systems.
Master Black Belt
in a Six Sigma program, a teacher and mentor for Black Belts; a full-time position.
Pareto analysis
a method for identifying the causes of poor quality, which usually shows that most quality problems result from only a few causes.
participative problem solving
involving employees directly in the quality-management process to identify and solve problems.
partnering
a relationship between a company and its supplier based on mutual quality standards.
prevention costs
costs incurred during product design and manufacturing that prevent nonconformance to specifications.
process flowchart
a diagram of the steps in a job, operation, or process.
production index
the ratio of quality cost to final product units.
productivity
a measure of effectiveness in converting resources into products, generally computed as output divided by input.
quality circles
a small, voluntary group (team) of workers and supervisors formed to address quality problems in their area.
quality impact on productivity
fewer defects increase output and quality improvement reduces inputs.
quality management system (QMS)
a system to achieve customer satisfaction that complements other company systems.
quality of conformance
the degree to which the product or service meets the specifications required by design during the production process.
quality of design
the degree to which quality characteristics are designed into a product or service.
quality-productivity ratio (QPR)
a productivity index that includes productivity and quality costs.
sales index
the ratio of quality cost to sales.
Six Sigma
a measure of how much a given product or process deviates from perfection, or zero defects; the basis of a quality-improvement program.
Six Sigma process
includes four basic steps—align, mobilize, accelerate and govern.
total quality management (TQM)
the management of quality throughout the organization at all management levels and across all areas.
yield
a measure of productivity; the sum of good-quality and reworked units.
SOLVED PROBLEMS
1. PRODUCT YIELD
A manufacturing company has a weekly product input of 1700 units. The average percentage of good-quality products is 83%. Of the poor-quality products, 60% can be reworked and sold as good-quality products. Determine the weekly product yield and the product yield if the good-product quality is increased to 92%.
• Animated Demo Problem
SOLUTION
Step 1. Compute yield according to the following formula:
Step 2. Increase %G to 92%:
2. QUALITY—PRODUCTIVITY RATIO
A retail telephone catalogue company takes catalogue orders from customers and then sends the completed orders to the warehouses to be filled. An operator processes an average of 45 orders per day. The cost of processing an order is $1.15, and it costs $0.65 to correct an order that has been filled out incorrectly by the operator. An operator averages 7% bad orders per day, all of which are reworked prior to filling the customer order. Determine the quality-productivity ratio for an operator.
SOLUTION
Compute the quality-productivity ratio according to the following formulas:
QUESTIONS
2-1. How does the consumer's perspective of quality differ from the producer's?
2-2. Briefly describe the dimensions of quality, for which a consumer looks in a product, and apply them to a specific product.
2-3. How does quality of design differ from quality of conformance?
2-4. Define the two major categories of quality cost and how they relate to each other.
2-5. What is the difference between internal and external failure costs?
2-6. A defense contractor manufactures rifles for the military. The military has exacting quality standards that the contractor must meet. The military is very pleased with the quality of the products provided by the contractor and rarely has to return products or has reason for complaint. However, the contractor is experiencing extremely high quality-related costs. Speculate on the reasons for the contractor's high quality-related costs.
2-7. Consider your school (university or college) as a production system in which the final product is a graduate. For this system:
a. Define quality from the producer's and customer's perspectives.
b. Develop a fitness-for-use description for final product quality.
c. Give examples of the cost of poor quality (internal and external failure costs) and the cost of quality assurance (prevention and appraisal) costs.
d. Describe how quality circles might be implemented in a university setting. Do you think they would be effective?
2-8. Discuss how a quality management program can affect productivity.
2-9. The Aurora Electronics Company has been receiving a lot of customer complaints and returns of a DVD player that it manufactures. When a DVD is pushed into the loading mechanism, it can stick inside and it is difficult to get the DVD out. Consumers will try to pull the DVD drawer out with their fingers or pry it out with an object such as a knife, pencil, or screwdriver, frequently damaging the DVD or hurting themselves. What are the different costs of poor quality and costs of quality assurance that might be associated with this quality problem?
2-10. What are the different quality characteristics you (as a consumer) would expect to find in the following three products: a DVD player, a pizza, running shoes?
2-11. AMERICARD, a national credit card company, has a toll-free, 24-hour customer service number. Describe the input for this system function and the final product. What quality-related costs might be associated with this function? What impact might a quality management program have on this area?
2-12. A number of quality management philosophies hold that prevention costs are the most critical quality-related costs. Explain the logic behind this premise.
2-13. Why is it important for companies to measure and report quality costs?
2-14. Describe the primary contribution to quality management of each of the following: W. E. Deming, Joseph Juran, Phillip Crosby, Armand Feigenbaum, and Kaoru Ishikawa.
2-15. Describe the impact that the creation of the Malcolm Baldrige Award has had on quality improvement in the United States.
2-16. Write a one- to two-page summary of an article from Quality Progress, about quality management in a company or organization.
2-17. More companies probably fail at implementing quality-management programs than succeed. Discuss the reasons why a quality-management program might fail.
2-18. Select a service company or organization and discuss the dimensions of quality on which a customer might evaluate it.
2-19. Select two competing service companies that you are familiar with or can visit, such as fast-food restaurants, banks, or retail stores, and compare how they interact with customers in terms of quality.
2-20. Develop a hypothetical quality-improvement program for the class in which you are using this textbook. Evaluate the class according to the dimensions of quality for a service. Include goals for quality improvement and ways to measure success.
2-21. Identify a company or organization from which you have received poor-quality products or services, describe the nature of the defects, and suggest ways in which you might improve quality.
2-22. Identify a company or organization from which you have received high-quality products and describe the characteristics that make them high-quality.
2-23. Explain why strategic planning might benefit from a TQM program.
2-24. Why has ISO 9000 become so important to U.S. firms that do business overseas?
2-25. Go to the Baldrige Award Web site, http://www.quality.nist.gov and research several companies that have won the Malcolm Baldrige Award. Describe any common characteristics that the quality-management programs in those companies have.
2-26. The discussion in this chapter has focused on the benefits of implementing a quality management program; however, many companies do not have such a program. Discuss the reasons why you think a company would not adopt a quality management program.
2-27. Access a Web site of a company that sells products to the general public on the Internet. Discuss the quality attributes of the site, and evaluate the quality of the Web site.
2-28. For an airline you have flown on list all of the quality “defects” you can recall. Discuss whether you think the airline exhibited overall good or poor quality. If it exhibited good quality, explain what made it so; if it exhibited poor quality, what actions do you think could be taken by the airline to improve quality?
2-29. Identify three Web sites that you think are poor quality and three that are good quality. What common characteristics are exhibited by the group of poor-quality sites? the group of good-quality sites? Compare the two groups.
2-30. The production and home delivery of a pizza is a relatively straightforward and simple process. Develop a fishbone diagram to identify potential defects and opportunities for poor quality in this process.
2-31. Most students live in a dormitory or apartment that they rent. Discuss whether this type of living accommodation is a product or service. Assess the quality of your living accommodation according to your previous response.
2-32. Develop a fishbone diagram for the possible causes of flight delays.
2-33. Observe a business with which you are familiar and interact with frequently, such as a restaurant or food service, a laundry service, your bank, or the college bookstore. Develop a Pareto chart that encompasses the major service defects of the business, identify the most significant service problems and suggest how quality could be improved.
2-34. County school buses are inspected every month for “defects.” In a recent monthly inspection, 27 worn or torn seats were found, 22 buses had dirty floors, there were 14 cases of exterior scratches and chipped paint, there were 8 cracked or broken windows, the engines on 4 buses had trouble starting or were not running smoothly, and 2 buses had faulty brakes. Develop a Pareto chart for the bus inspections and indicate the most significant quality-problem categories. What does this tell you about the limitations of applying Pareto chart analysis. How might these limitations be overcome in Pareto chart analysis?
2-35. Joseph Juran created a “quality spiral” showing that each element of the business process, each function, not just the end product, is important. Describe how each of the following business process areas might impact quality: marketing, engineering, purchasing/sourcing, human resources, and distribution.
2-36. Referring to Table 2.3, research the winner of an international quality award at one of the award Web sites and write a brief report.
2-37. Go to the Malcolm Baldrige Award Web site, www.quality.nist.gov, and write a brief report on one of the most recent years' Baldrige Award winners similar to the “Along the Supply Chain” boxes in this chapter.
2-38. Write a brief summary on the application of quality management in a company from Qualityworld, a professional trade magazine published in the United Kingdom.
2-39. Develop a fishbone diagram for the possible causes of your car not starting.
2-40. Describe the differences between Black Belts, Green Belts, and Master Black Belts in a Six Sigma program.
2-41. Describe the steps in the Six Sigma breakthrough strategy for quality improvement.
2-42. Develop a quality-improvement project in a situation you are familiar with such as a current or former job, a part-time job, a restaurant, your college bookstore, your dorm or apartment, a local business, and so on, and describe how you would apply the steps of the six sigma breakthrough strategy.
2-43. Reference the Web site for the American Customer Satisfaction Index (ACSI) at www.theacsi.org and write a brief summary describing how the numerical ACSI value is determined. Also, select an industry or service sector and pick two companies, one with a high ACSI and one with a relatively low ACSI: using your own knowledge and research about the companies, explain why you think they have different ACSI values.
2-44. Develop a Six Sigma-type quality improvement project employing the DMAIC steps for your own personal health such as losing weight, improving your diet, exercise, etc.
2-45. Develop a Six Sigma-type project employing the DMAIC steps for improving any phase of your personal life that you feel may be “defective.”
2-46. Visit your university infirmary and study the process in-patients follow to see a doctor and describe a quality improvement project to improve this process.
2-47. At most universities course registration for future semesters typically involves some type of computerized online process possibly combined with some personal consultation with an academic advisor. Describe the registration process in your academic college or at your university and suggest ways the process could be improved.
2-48. The Japanese are generally credited with starting the global quality revolution that in the 1970s became an integral part of corporate culture, and eventually led to the development of quality improvement programs systems like TQM and Six Sigma. Research and write a report about what Japan did to initiate the quality movement and why it differed from what was being done in the United States.
2-49. Describe the general steps a company must go through to obtain ISO 9001:2008 certification.
2-50. Select a retail store you are familiar with such as a grocery store, J. Crew, Macy's, Best Buy, Target, etc., and identify what might be considered as “defects” in their processes and how improvement might be measured.
2-51. ISO 9000 and the Malcolm Baldrige Award competition are both programs that seek to achieve recognition for outstanding quality, one in the form of a certificate and the other in the form of an award. Discuss how the two are similar and different, and how they might complement each other.
2-52. Explain how you would determine customer satisfaction with a bank, your university, a football game, an airline, a car, a cell phone, and a television. Describe the tools and processes you would use to measure customer satisfaction.
2-53. In the ongoing national debate about health care that is likely to continue for years, one view holds that quality improvement (and corresponding cost reduction) across the industry is fundamentally not possible because the direct consumer (i.e., the patient) is not who pays the bill, for most people the insurance company is. Since insurance companies do not directly receive the service provided, they cannot assess how well “value” is being delivered, and neither the customer nor the insurance company are motivated to reduce costs. Discuss this phenomenon of the health-care industry and make a case for why you think it is accurate or inaccurate. Also address in your discussion how health-care insurance differs from other forms of personal insurance.
PROBLEMS
• GO Tutoriat
2-1. Backwoods American, Inc., produces expensive water-repellent, down-lined parkas. The company implemented a total quality-management program in 2005. Following are quality-related accounting data that have been accumulated for the five-year period after the program's start
Year
2006
2007
2008
2009
2010
Quality Costs (000s)
Prevention
$3.2
10.7
28.3
42.6
50.0
Appraisal
26.3
29.2
30.6
24.1
19.6
Internal failure
39.1
51.3
48.4
35.9
32.1
External failure
118.6
110.5
105.2
91.3
65.2
Accounting Measures (000s)
Sales
$2,700.6
2,690.1
2,705.3
2,310.2
2,880.7
Manufacturing
cost
420.9
423.4
424.7
436.1
435.5
a. Compute the company's total failure costs as a percentage of total quality costs for each of the five years. Does there appear to be a trend to this result? If so, speculate on what might have caused the trend.
b. Compute prevention costs and appraisal costs, each as a percentage of total costs, during each of the five years. Speculate on what the company's quality strategy appears to be.
c. Compute quality-sales indices and quality-cost indices for each of the five years. Is it possible to assess the effectiveness of the company's quality-management program from these index values?
d. List several examples of each quality-related cost—that is, prevention, appraisal, and internal and external failure—that might result from the production of parkas.
2-2. The Backwoods American company in Problem 2-1 produces approximately 20,000 parkas annually. The quality management program the company implemented was able to improve the average percentage of good parkas produced by 2% each year, beginning with 83% good-quality parkas in 2003. Only about 20% of poor-quality parkas can be reworked.
a. Compute the product yield for each of the five years.
b. Using a rework cost of $12 per parka, determine the manufacturing cost per good parka for each of the five years. What do these results imply about the company's quality management program?
2-3. The Colonial House Furniture Company manufactures two-drawer oak file cabinets that are sold unassembled through catalogues. The company initiates production of 150 cabinet packages each week. The percentage of good-quality cabinets averages 83% per week, and the percentage of poor-quality cabinets that can be reworked is 60%.
a. Determine the weekly product yield of file cabinets.
b. If the company desires a product yield of 145 units per week, what increase in the percentage of good-quality products must result?
2-4. In Problem 2-3, if the direct manufacturing cost for cabinets is $27 and the rework cost is $8, compute the manufacturing cost per good product. Determine the manufacturing cost per product if the percentage of good-quality file cabinets is increased from 83% to 90%.
2-5. The Omega Shoe Company manufactures a number of different styles of athletic shoes. Its biggest seller is the X-Pacer running shoe. In 2008 Omega implemented a quality-management program. The company's shoe production for the past three years and manufacturing costs are as follows.
Year
2008
2009
2010
Units produced/input
32,000
34,600
35,500
Manufacturing cost
$278,000
291,000
305,000
Percent good quality
78%
83%
90%
Only one-quarter of the defective shoes can be reworked, at a cost of $2 apiece. Compute the manufacturing cost per good product for each of the three years and indicate the annual percentage increase or decrease resulting from the quality-management program.
2-6. The Colonial House Furniture Company manufactures four-drawer oak filing cabinets in six stages. In the first stage, the boards forming the walls of the cabinet are cut: in the second stage, the front drawer panels are wood-worked: in the third stage, the boards are sanded and finished: in the fourth stage, the boards are cleaned, stained, and painted with a clear finish; in the fifth stage, the hardware for pulls, runners, and fittings is installed; and in the final stage, the cabinets are assembled. Inspection occurs at each stage of the process, and the average percentages of good-quality units are as follows.
Stage
Average Percentage Good Quality
1
87%
2
91%
3
94%
4
93%
5
93%
6
96%
The cabinets are produced in weekly production runs with a product input for 300 units.
a. Determine the weekly product yield of good-quality cabinets.
b. What would weekly product input have to be in order to achieve a final weekly product yield of 300 cabinets?
2-7. In Problem 2-6, the Colonial House Furniture Company has investigated the manufacturing process to identify potential improvements that would improve quality. The company has identified four alternatives, each costing $15,000, as follows.
Alternative
Quality Improvement
1
Stage 1: 93%
2
Stage 2: 96%. Stage 4: 97%
3
Stage 5: 97%, Stage 6: 98%
4
Stage 2: 97%%
a. Which alternative would result in the greatest increase in product yield?
b. Which alternative would be the most cost effective?
2-8. The Backwoods American company operates a telephone order system for a catalogue of its outdoor clothing products. The catalogue orders are processed in three stages. In the first stage, the telephone operator enters the order into the computer; in the second stage, the items are secured and batched in the warehouse; and in the final stage, the ordered products are packaged. Errors can be made in orders at any of these stages, and the average percentage of errors that occurs at each stage are as follows.
Stage
% Errors
1
12%
2
8%
3
4%
If an average of 320 telephone orders are processed each day, how many errorless orders will result?
2-9. The total processing cost for producing the X-Pacer running shoe in Problem 2-5 is $18. The Omega Shoe Company starts production of 650 pairs of the shoes weekly, and the average weekly yield is 90%, with 10% defective shoes. One quarter of the defective shoes can be reworked at a cost of $3.75.
a. Compute the quality-productivity ratio (QPR).
b. Compute the QPR if the production rate is increased to 800 pairs of shoes per week.
c. Compute the QPR if the processing cost is reduced to $16.50 and the rework cost to $3.20.
d. Compute the QPR if the product yield is increased to 93% good quality.
2-10. Airphone, Inc., manufactures cellular telephones at a processing cost of $47 per unit. The company produces an average of 250 phones per week and has a yield of 87% good-quality phones, resulting in 13% defective phones, all of which can be reworked. The cost of reworking a defective telephone is $16.
a. Compute the quality-productivity ratio (QPR).
b. Compute the QPR if the company increased the production rate to 320 phones per week while reducing the processing cost to $42, reducing the rework cost to $12, and increasing the product yield of good-quality telephones to 94%.
2-11. Burger Doodle is a fast-food restaurant that processes an average of 680 food orders each day. The average cost of each order is $6.15. Four percent of the orders are incorrect, and only 10% of the defective orders can be corrected with additional food items at an average cost of $1.75. The remaining defective orders have to be thrown out.
a. Compute the average product cost.
b. In order to reduce the number of wrong orders, Burger Doodle is going to invest in a computerized ordering and cash register system. The cost of the system will increase the average order cost by $0.05 and will reduce defective orders to 1%. What is the annual net cost effect of this quality-improvement initiative?
c. What other indirect effects on quality might be realized by the new computerized order system?
2-12. Compute the quality–productivity ratio (QPR) for the Burger Doodle restaurant in parts (a) and (b) in Problem 2-11.
2-13. For the Medtek Company in Example 2.1, determine the break-even point (in sales) and draw the break-even diagram for both cases described in the example—with defects and without. (Refer to Chapter 6, “Processes and Technology,” for a description of break-even analysis). Discuss the significance of the difference between the two break-even points.
2-14. The Blue Parrot is an expensive restaurant in midtown open only for dinner. Entrees are set at a fixed price of $42. In a typical month the restaurant will serve 3,600 entrees. Monthly variable costs are $61,200, and fixed costs are $31,000 per month. Customers or waiters send back 8% of the entrees because of a defect, and they must be prepared again; they cannot be reworked. The restaurant owners hired a qualified black belt to undertake a Six Sigma project at the restaurant to eliminate all defects in the preparation of the entrees (i.e., 3.4 DPMO). Compare the profit in both situations, with and without defects, and indicate both the percentage decrease in variable costs and the percentage increase in profits following the Six Sigma project. Assuming that the restaurant paid the black belt $25,000 to achieve zero defects, and the restaurant owners plan to amortize this payment over a three-year period (as a fixed cost), what is the restaurant return on its investment (without applying an interest rate)? Discuss some other aspects of quality improvement at the restaurant that might result from the Six Sigma project.
2-15. A black belt has identified the following key input (X) and output (Y) variables for the process of laundering your clothes in your washing machine at home:
Input (X) Variables
Output (Y) Variables
Sort laundry
Clothes clean
Cycle
Clothes not damaged
Wash temperature
Colors okay
Rinse temperature
Lint free
Stain treatment
Stains removed
Load size
Smell fresh/no odors
Fabric softener
Detergent
Bleach
Type of washer
Develop a cause-and-effect diagram for this process of washing clothes. Next develop a cause-and-effect matrix and use your own insight and judgment about the process to rank and weight the output (Y) variables, assign a numerical score to each X-Y combination, develop overall scores for each X variable, and then rank the X variables in terms of importance.
2-16. A retail Web site sells a variety of products including clothes, electronics, furniture, sporting goods, books, video games, CDs and DVDs, among other items. An average customer order is $47. Weekly total variable costs are $365,000 and weekly fixed costs are $85,000. The company averages 18,400 orders per week and 12% of all orders are returned for a variety of reasons besides the customer not liking the product, including product misinformation on the Web site, errors in fulfilling the order, incomplete orders, defective product, breakage, etc. Thirty percent of all returned orders are turned around and refilled correctly per the customer's desire, but at a cost (for handling, packaging, and mailing) of $8 per order, while the remaining 70% of returned orders are lost. In addition, it is estimated that half of the customers associated with lost orders will not return to the Web site at a cost of $15 per order. Determine the weekly cost of poor quality for the Web site. The company can implement a quality improvement program for $800,000 a year that will reduce the percentage of returned orders to 2%; should the company invest in the program? How should the company address its quality problem, i.e., what processes does it likely need to improve? Why would zero defects not eliminate returned orders?
CASE PROBLEM 2.1
Designing a Quality-Management Program for the internet at D4Q
Design for Quality (D4Q) is a consulting firm that specializes in the design and implementation of quality management programs for service companies and organizations. It has had success designing quality programs for retail stores and catalogue order services. Recently D4Q was approached by a catalogue order company, BookTek Media, Inc., with the offer of a job. BookTek sells books, CDs, DVDs, and videos through its mail-order catalogue operation. BookTek has decided to expand its service to the Internet. BookTek is experienced in catalogue telephone sales and has a successful quality-management program in place. Thus, the company is confident that it can process orders and make deliveries on time with virtually no errors.
A key characteristic of BookTek's quality management program is the company's helpful, courteous, and informative phone representatives. These operators can answer virtually any customer question about BookTek's products, with the help of an information system. Their demeanor toward customers is constantly monitored and graded. Their telephone system is so quick that customers rarely have to wait for a representative to assist them. However, the proposed Internet ordering system virtually eliminates direct human contact with the customer. Since there will be no human contact, BookTek is concerned about how it will be able to make customers feel that they are receiving high-quality service. Furthermore, the company is unsure how its employees can monitor and evaluate the service to know if the customer thinks it is good or poor. The primary concern is how to make customers feel good about the company in such an impersonal, segregated environment. At this point BookTek is unconcerned with costs; management simply wants to develop the highest-quality, friendliest Web site possible.
D4Q indicated that it would like to take on the job, but while it is familiar with BookTek's type of catalogue order system, it is relatively unfamiliar with how things are ordered on the Internet for this kind of retail book business. It suggested that its first order of business might be to investigate what other companies were doing on the Internet.
Help D4Q develop a quality management plan for BookTek. Include in your plan the quality dimensions and characteristics of an Internet ordering system specifically for BookTek's products, suggestions for achieving customer satisfaction, ways to measure defective service, and how to evaluate the success of the order system in terms of quality.
CASE PROBLEM 2.2
Quality Management at State University
As a result of several years of severe cuts to its operating budget by the state legislature, the administration at State University has raised tuition annually for the past five years. Five years ago getting an education at State was a bargain for both in-state and out-of-state students; now it is one of the more expensive state universities. An immediate repercussion has been a decline in applications for admission. Since a portion of state funding is tied to enrollments, State has kept its enrollments up at a constant level by going deeper into its pool of applications, taking some less-qualified students.
The increase in the cost of a State degree has also caused legislators, parents, and students to be more conscious of the value of a State education—that is, the value parents and students are receiving for their money. This increased scrutiny has been fueled by numerous media reports about the decreased emphasis on teaching in universities, low teaching loads by faculty, and the large number of courses taught by graduate students. This, in turn, has led the state legislature committee on higher education to call for an “outcomes assessment program” to determine how well State University is achieving its mission of producing high-quality graduates.
On top of those problems, a substantial increase in the college-age population is expected this decade, resulting from a “baby boom” during the 1990s. Key members of the state legislature have told the university administration that they will be expected to absorb their share of the additional students during the next decade. However, because of the budget situation, they should not expect any funding increases for additional facilities, classrooms, dormitory rooms, or faculty. In effect, they will be expected to do more with their existing resources. State already faces a classroom deficit, and faculty have teaching loads above the average of its peer institutions. Legislators are fond of citing a study that shows that if the university simply gets all the students to graduate within a four-year period or reduces the number of hours required for graduation, they can accommodate the extra students.
This entire scenario has made the university president, Fred McMahan, consider retirement. He has summarized the problems to his administration staff as “having to do more, better, with less.” One of the first things he did to address these problems was to set up a number of task forces made up of faculty and administrators to brainstorm a variety of topics. Among the topics and problems these task forces addressed were quality in education, educational success, graduation rates, success rates in courses (i.e., the percentage of students passing), teaching, the time to graduation, faculty issues, student issues, facilities, class scheduling, admissions, and classroom space.
Several of the task forces included faculty from engineering and business. These individuals noted that many of the problems the university faced would benefit from the principles and practices of a quality management approach. This recommendation appealed to Fred McMahan and the academic vice president, Anne Baker.
Discuss in general terms how a quality philosophy and practices might be instituted at State University.
CASE PROBLEM 2.3
Quality Problems at the Tech Bookstores
Tech is a major state university located in a small, rural coltege town. Tech Services is an incorporated university entity that operates two bookstores, one on campus and one off campus at a nearby mall. The on-campus store sells school supplies, textbooks, and school-licensed apparel and gifts and it has a large computer department. The off-campus store sells textbooks, school supplies, and licensed apparel and gifts and it has a large trade book department. The on-campus store has very limited parking, but it is within easy walking distance of the downtown area, all dormitories, and the football stadium and basketball arena. The off-campus store has plenty of parking, but it is not within walking distance of campus, although it is on the town bus line. Both stores compete with several other independent and national chain college bookstores in the town plus several school supply stores, apparel stores, computer stores, and trade bookstores. The town and university have been growing steadily over the past decade, and the football team has been highly ranked and gone to a bowl for eight straight seasons.
The Tech bookstores have a long-standing policy of selling textbooks with a very small markup (just above cost), which causes competing stores to follow suit. However, because textbooks are so expensive anyway most students believe the Tech bookstores gouge them on textbook prices. In order to offset the tack of profit on textbooks, the Tech bookstores sell all other products at a relatively high price. All “profits” from the stores are used to fund student-related projects such as new athletic fields and student center enhancements.
Tech Services has a Board of Directors made up of faculty, administrators, and students. The executive director, Mr. David Watson, reports to the Board of Directors and oversees the operation of the bookstores (plus all on-campus vending and athletic event vending). His office is in the on-campus store. Both bookstores have a store manager and an assistant store manager. There is one textbook manager for both stores, a trade book manager, a single school supplies and apparel manager, and a computer department manager, as well as a number of staff people, including a computer director and staff, a marketing director, a finance staff, a personnel director, a warehouse manager and secretaries. Almost all of the floor employees including cash register operators, sales clerks, stock people, delivery truck drivers, and warehouse workers, are part-time Tech students. Hiring Tech students has been a long-standing university policy in order to provide students with employment opportunities. The bookstores have a high rate of turnover among the student employees, as would be expected.
Several incidents have occurred at the off-campus store that have caused the Tech Services Board of Directors concern. In one incident a student employee was arrested for drug possession. In another incident a faculty customer and student employee got into a shouting match when the employee could not locate a well-known book on the bookstore computer system and the faculty member got frustrated over the time it was taking. In still another incident an alumnus who had visited the store after a football game sent a letter to the university president indicating that a student employee had been rude to him when he asked a question about the return policy for an apparel item he had purchased on the bookstore's Web site. When the student did not know the return policy, he told the customer in a condescending manner to come back later. The last incident was an offhand remark made by a local town resident to a Board member at a party about the difficulty she had completing a purchase at the mall store because the registers were unmanned, although she could see several employees talking together in the store.
Although sales and profits at the bookstore have been satisfactory and steady over the past few years, the Board of Directors is extremely sensitive to criticism about anything that might have the potential to embarrass the university. The Board of Directors suggested to Mr. Watson that he might consider some type of assessment of the service at the bookstores to see if there was a problem. Mr. Watson initially attempted to make random, surprise visits to the bookstores to see if he could detect any problems; however, there seemed to be a jungle telegraph system that alerted his employees whenever he entered a store, so he abandoned that idea. Next he decided to try two other things. First he conducted a customer survey during a two-week period in the middle of the semester at both stores. As customers left the store, he had employees ask them to respond to a brief questionnaire. Second, he hired several graduate students to pose as customers and make purchases and ask specific questions of sales clerks, and report on their experiences.
Selected results from the customer survey are on the table below.
The only consistent responses from the graduate students posing as customers were that the student employees were sometimes not that familiar with store policies, how to operate the store computer systems, what products were available, and where products were located in the stores. When they didn't know something they sometimes got defensive. A few also said that students sometimes appeared lackadaisical and bored.
Using observations of the operation of your own college bookstores to assist you, answer the following questions.
a. Why do you think Mr. Watson organized the customer survey the way he did? What other things do you think he might have done to analyze the stores' quality problems?
CAMPUS STORE
OFF-CAMPUS STORE
Student
Nonstudent
Student
Nonstudent
Yes
No
Yes
No
Yes
No
Yes
No
Were employees courteous and friendly?
572
93
286
147
341
114
172
156
Were employees knowledgeable and helpful?
522
143
231
212
350
105
135
193
Was the overall service good?
569
96
278
165
322
133
180
148
Did you have to wait long for service?
74
591
200
243
51
404
150
178
Did you have to wait long to check out?
81
584
203
240
72
383
147
181
Was the item you wanted available?
602
63
371
72
407
48
296
32
Was the cost of your purchase(s) reasonable?
385
280
398
45
275
180
301
27
Have you visited the store's Web site?
335
330
52
391
262
193
17
311
b. Develop Pareto charts to help analyze the survey results.
c. How would you define quality at the bookstores?
d. Discuss what you believe are the quality problems the bookstores have?
e. What are the bookstores' costs of poor quality?
f. What actions or programs would you propose to improve quality at the bookstores?
g. What obstacles do you perceive might exist to hinder changes at the bookstores and quality improvement?
h. What benefits do you think would result from quality improvement at the bookstores?
CASE PROBLEM 2.4
Product Yield at Continental Luggage Company
The Continental Luggage Company manufactures several different styles of soft- and hardcover luggage, briefcases, hanging bags, and purses. Their best-selling item is a line of hardcover luggage called the Trotter. It is produced in a basic five-stage assembly process that can accommodate several different outer coverings and colors. The assembly process includes constructing a heavy-duty plastic and metal frame; attaching the outer covering; joining the top and bottom and attaching the hinge mechanism; attaching the latches, lock, and handle; and doing the finishing work, including the luggage lining.
The market for luggage is extremely competitive, and product quality is a very important component in product sales and market share. Customers normally expect luggage to be able to withstand rough handling while retaining its shape and an attractive appearance and protecting the clothing and personal items inside the bag. They also prefer the bag to be lightweight and not cumbersome. Furthermore, customers expect the latches and locks to work properly over an extended period of time. Another key factor in sales is that the luggage must be stylish and visually appealing.
Assembly Stage
Average Percentage Good Quality
Average Percentage Reworked
1
0.94
0.23
2
0.96
0.91
3
0.95
0.67
4
0.97
0.89
5
0.98
0.72
Because of the importance of quality, company management has established a process control procedure that includes inspection at each stage of the five major stages of the assembly process. The following table shows the percentage of good-quality units yielded at each stage of the assembly process and the percentage of bad units that can be reworked, on average.
The first stage of the process is construction of the frame, and it is very difficult to rework the frame if an item is defective, which is reflected in the low percentage of reworked items.
Five hundred new pieces of luggage of a particular style and color are initiated through the assembly process each week. The company would like to know the weekly product yield and the number of input units that would be required to achieve a weekly yield of 500 units. Furthermore, the company would like to know the impact on product yield (given 500 initial starting units) if a quality-improvement program were introduced that would increase the average percentage of good-quality units at each stage by 1%.
Chapter 7 Capacity and Facilities Design
Web resources for this chapter include
▸ OM Tools Software
▸ Internet Exercises
▸ Online Practice Quizzes
▸ Lecture Slides in PowerPoint
▸ Virtual Tours
▸ Excel Exhibits
▸ Company and Resource Weblinks
www.wiley.com/college/russell
In this chapter, you will learn about...
• Capacity Planning
• Facilities
• Basic Layouts
• Designing Process Layouts
• Designing Service Layouts
• Designing Product Layouts
• Hybrid Layouts
Capacity and Facilities Design AT THE NEW ENGLAND CONFECTIONERY COMPANY
ECCO (THE NEW ENGLAND CONFECTIONERY COMPANY) is the oldest multiline candy manufacturer in the United States, best known for its popular “conversational” line of candy hearts. In recent years, the company has closed its venerable Boston facility and consolidated three other facilities into a state-of-the art manufacturing and distribution center in Revere, Massachusetts.
The move enabled the company to completely reassess every step of its production process, including work flow and staffing, to come up with a new layout design that moved candy more quickly from the factory floor to the customer. The new 820,000-square-foot facility is home to 586,000 square feet of production area, 200,000 square feet of warehouse space, and 30,000 square feet of office space. The facility has over 30 different process lines capable of manufacturing over 70 million pounds of candy per year. The building has two stories, with processing operations on the second floor feeding packaging operations on the first floor. A key to cutting cycle times was eliminating the extremely long assembly lines that snaked through the old building and establishing more efficient work cells with smaller assembly lines where workers have access to everything they need.
By consolidating three facilities into one, NECCO's delivery time to the customer improved significantly. The company puts each of its top candy lines into one of three categories, based on ABC analysis (see Chapter 13). Customer orders for A items can be delivered in 5 days, B items in 10 days, and C items in 15 days. The new facility also has allergen rooms for panning chocolate to isolate products with nuts from those without, an important requirement for many of today's consumers. Visitors agree that the new plant is clean, well organized, and high-tech. The process of designing the new facility allowed NECCO to better meet regulations, reduce operating costs, expand capacity, improve customer service, and grow its business.
Effective facility design can have immeasurable benefits to a company. In this chapter, we'll talk about the importance of facility design and explore different types of facility layouts for both manufacturing and service operations.
Source: David Weldon, “Sweet Surroundings,” Food and Drink Digital, July 2007, and the NECCO company Web site at www.necco.com.
CAPACITY PLANNING
Capacity is the maximum capability to produce. Capacity planning takes place at several levels of detail. We discuss long-term capacity planning in this chapter, intermediate term capacity planning in Chapter 14, and short-term capacity planning in Chapters 15 and 16.
Capacity:
the maximum capability to produce.
Long-term capacity planning is a strategic decision that establishes a firm's overall level of resources. It extends over a time horizon long enough to obtain those resources—usually a year or more for building or expanding facilities or acquiring new businesses. Capacity decisions affect product lead times, customer responsiveness, operating costs, and a firm's ability to compete. Inadequate capacity can lose customers and limit growth. Excess capacity can drain a company's resources and prevent investments in more lucrative ventures. When to increase capacity and how much to increase it are critical decisions.
Capacity planning:
establishes the overall level of productive resources for a firm.
Figure 7.1 a, b, and c show three basic strategies for the timing of capacity expansion in relation to a steady growth in demand.
• Capacity lead strategy . Capacity is expanded in anticipation of demand growth. This aggressive strategy is used to lure customers from competitors who are capacity constrained or to gain a foothold in a rapidly expanding market. It also allows companies to respond to unexpected surges in demand and to provide superior levels of service during peak demand periods.
• Average capacity strategy . Capacity is expanded to coincide with average expected demand. This is a moderate strategy in which managers are certain they will be able to sell at least some portion of expanded output, and endure some periods of unmet demand. Approximately half of the time capacity leads demand, and half of the time capacity lags demand.
As demand grows, a lead, lag, or average capacity strategy can be applied.
• Capacity lag strategy . Capacity is increased after an increase in demand has been documented. This conservative strategy produces a higher return on investment but may lose customers in the process. It is used in industries with standard products and cost-based or weak competition. The strategy assumes that lost customers will return from competitors after capacity has expanded.
Figure 7.1 Capacity Expansion Strategies
Consider higher education's strategy in preparing for a tripling of the state's college-bound population in the next decade. An established university, guaranteed applicants even in lean years, may follow a capacity lag strategy. A young university might lead capacity expansion in hopes of capturing students not admitted to the more established universities. A community college may choose the average capacity strategy to fulfill its mission of educating the state's youth but with little risk.
Capacity can be increased incrementally or in large steps.
How much to increase capacity depends on (1) the volume and certainty of anticipated demand; (2) strategic objectives in terms of growth, customer service, and competition; and (3) the costs of expansion and operation.
Capacity can be increased incrementally or in one large step as shown in Figure 7.1 d . Incremental expansion is less risky but more costly. An attractive alternative to expanding capacity is outsourcing, in which suppliers absorb the risk of demand uncertainty.
The best operating level for a facility is the percent of capacity utilization that minimizes average unit cost. Rarely is the best operating level at 100% of capacity—at higher levels of utilization, productivity slows and things start to go wrong. Average capacity utilization differs by industry. An industry with an 80% average utilization would have a 20% capacity cushion for unexpected surges in demand or temporary work stoppages. Large-capacity cushions are common in industries in which demand is highly variable, resource flexibility is low, and customer service is important. Utilities, for example, maintain a 20% capacity cushion. Capital-intensive industries with less flexibility and higher costs maintain cushions under 10%. Airlines maintain a negative cushion by overbooking flights. Best operating level can also refer to the most economic size of a facility.
Best operating level:
is the percent of capacity utilization that minimizes unit costs.
Capacity cushion:
is the percent of capacity held in reserve for unexpected occurrences.
Figure 7.2 shows the best operating level—in this case, the number of rooms for a hotel—as the point at which the economies of scale have reached their peak and the diseconomies of scale have not yet begun.
Diseconomies of scale:
when higher levels of output cost more per unit to produce.
Economies of scale occur when it costs less per unit to produce or operate at high levels of output. This holds true when:
Economies of scale:
when it costs less per unit to produce high levels of output.
• Fixed costs can be spread over a larger number of units.
• Production or operating costs do not increase linearly with output levels,
Figure 7.2 Best Operating Level for a Hotel
• Quantity discounts are available for material purchases, and
• Operating efficiency increases as workers gain experience.
The electronics industry provides a good case example of economies of scale. The average cost per chip placement for printed circuit-board assembly is 32 cents in factories with a volume of 25 million placements, 15 cents in factories with 200 million placements, and only 10 cents in factories with 800 million placements.1
Capacity decisions provide a framework for further facility decisions, such as where to locate a new facility and how to arrange the flow of work in the facility. Facility location is discussed in the supplement to this chapter. The remainder of the chapter presents various alternatives for laying out a facility.
Kuala Lumpur International (KLIA) is a Green certified airport with spectacular architecture. Shown here, the outside of the terminals resemble Bedouin tents. Inside, trees and other vegetation, along with waterfalls and streams, recreate a rain forest environment. The airport can handle 25 million passengers a year, and is a major cargo hub for the Asian-Pacific region.
1 “High Volumes Yield Profits for High-Tech Factories.” HE Solutions (April 1996), p. 8.
FACILITIES
Facilities make a difference. They can provide a competitive edge by enabling and leveraging the latest process concepts. For example, Bank of America, featured in the “Along the Supply Chain” box has created an exemplary facility showcasing green design. Green buildings can save energy costs and increase worker productivity. Facility design has an impact on both quality and productivity. Facilities affect how efficiently workers can do their jobs, how much and how fast goods can be produced, how difficult it is to automate a system, and how responsive the system can be to changes in product or service design, product mix, or demand volume. Facilities must be planned, located, and laid out.
Facility layouts are more flexible than ever before. Factories that once positioned shipping and receiving departments at one end of the building, now construct t-shaped buildings so that deliveries can be made directly to points of use within the factory. Stores sport portable kiosks for customer inquiry and checkout at various locations throughout the facility. Classrooms incorporate desks on wheels to be repositioned for different teaching styles and student interaction. Effective layouts can have many different objectives.
OBJECTIVES OF FACILITY LAYOUT
Facility layout refers to the arrangement of activities, processes, departments, workstations, storage areas, aisles, and common areas within an existing or proposed facility. The basic objective of the layout decision is to ensure a smooth flow of work, material, people, and information through the system. Effective layouts also:
Facility layout:
the arrangement of areas within a facility.
• Minimize movement and material handling costs;
Facility layout decisions involve multiple objectives.
• Utilize space efficiently;
• Utilize labor efficiently;
• Eliminate bottlenecks;
• Facilitate communication and interaction between workers, between workers and their supervisors, and between workers and customers;
• Reduce manufacturing cycle time and customer service time;
• Eliminate wasted or redundant movement;
• Facilitate the entry, exit, and placement of material, products, and people;
• Incorporate safety and security measures;
• Promote product and service quality;
• Encourage proper maintenance activities;
• Provide a visual control of activities;
• Provide flexibility to adapt to changing conditions;
• Increase capacity.
Layout decisions affect quality and competitiveness.
ALONG THE SUPPLY CHAIN Bank of America's Towering Achievement in Green Design
Green facility design is evolving fast, demanding that designers and builders adapt to new methods and technologies with every project. To date, the Bank of America Tower in New York City is the world's greenest skyscraper. Its unprecedented use of recycled and energy-saving materials in construction, along with incredible advances in water and energy efficiency, earned the building a platinum certification under the LEED (Leadership in Energy and Environment Design) rating system. LEED is part of the U.S. Green Building Council's code for the best practices, materials, and systems in green buildings. A platinum rating is the Council's highest measure of achievement.
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While Bank of American (BoA) estimates it costs an extra 5%, or around $65 million, to green the building, with millions of dollars in energy savings each year, and tens of millions in savings from fewer sick days and increased productivity, the project is expected to pay for itself within two to three years.
Nearly 48 inches of rain falls on New York City every year. At BoA Tower, most of this water is recycled for the building's use. The tower funnels precipitation from its tall slanting roofs and low green-roofed atrium into four holding tanks. The tanks, positioned at various locations throughout the building's core, are used to feed the A/C system, flush toilets, and irrigate plants. Water is also harvested from condensation on the air conditioning system, and from the small flow of groundwater that seeps through the bedrock of the tower's basement. With rainwater capture, clean water recycling and water conservation (such as waterless urinals), BoA expects to save 10.3 million gallons of water per year, enough to meet the annual water needs of 125 households.
Studies show that students and workers perform better in fresh-air, naturally-lit environments. At BoA Tower, 9.5-foot-tall floor-to-ceiling windows made of “low iron” glass are both more transparent and more insulating than conventional glass. Transparent walls separating work areas flood the building with light and give most workers some view of daylight. Ceiling-mounted photo and motion sensors continually adjust overhead lights, turning them down when natural light is bright or when rooms are empty. The system helps the building cut its demand for electric lighting by 25%.
It is a fact that heat rises. Yet most buildings pump cooled air into overhead ductwork and extract warm air through another set of ceiling exhaust vents. At BoA tower, one set of ductworks is eliminated. Cool air is pumped into a space below the building's raised floors. As workers and office equipment warm the air in their workspace, the heated air rises to the ceiling exhaust vents. This in turn pulls chilled air up from below. The system improves air quality, as well, by eliminating miles of chilled, moist ductwork, where bacteria, mold, and mildew often grow.
Clean, oxygen-rich air delivers big productivity gains. The BoA tower acts like a 55-story air purifier, with filters that catch 95% of particulate matter, allergens, ozone, and other compounds that can cause illness. Oxygen sensors trigger injections of fresh air into crowded spaces to energize workers and prevent “meeting room coma.”
Shipping electricity via power lines over long distances can waste 70% of the fuel's energy. Not so at BoA tower where they make most of their own electricity. Inside the tower's podium level is a super-efficient 5.1 megawatt power plant running on clean-burning natural gas, and housed in the smaller of the two spires of the tower is a wind turbine. Together these power sources generate enough energy to meet four-fifths of the tower's peak needs.
Reducing peak energy needs is another one of BoA's goals. To chill the A/C system, the tower makes ice during nonpeak periods and stores it in 44 10′ × 10′ cylindrical ice tanks. The old-fashioned ice-house cuts power consumption by 50% during the hottest of summer days.
Normally, a tower of this scale built in New York City would include hundreds of basement parking spots. By design, at BoA Tower, there are zero parking spaces. Instead, new pedestrian tunnels connect the building to 17 subway lines, more than any other station in New York City. The tower also has secure bike storage and shower access for those employees bicycling to work.
The Bank of America Tower in New York City is not only a visually stunning 1000-foot-tall skyscraper built in the heart of Manhattan; it is also a model of environmental awareness in facility design and operation.
Find out which buildings in your area are LEED certified.
Source: Adapted from Adam Ashton, “Bank of America's Bold Statement in Green,” Business Week, March 19, 2007, pp. 22-23.
BASIC LAYOUTS
Layouts can take many different forms. In the next section, we discuss three basic layout types: process, product, and fixed-position. Later in the chapter, we discuss three hybrid layouts: cellular layouts, flexible manufacturing systems, and mixed-model assembly lines.
PROCESS LAYOUTS
Process layouts, also known as functional layouts, group similar activities together in departments or work centers according to the process or function they perform. For example, in a machine shop, all drills would be located in one work center, lathes in another work center, and milling machines in still another work center. In a department store, women's clothes, men's clothes, children's clothes, cosmetics, and shoes are located in separate departments. A process layout is characteristic of intermittent operations, service shops, job shops, or batch production, which serve different customers with different needs. The volume of each customer's order is low, and the sequence of operations required to complete a customer's order can vary considerably.
Figure 7.3 A Process Layout in Services
Process layouts:
group similar activities together according to the process or function they perform.
The equipment in a process layout is general purpose, and the workers are skilled at operating the equipment in their particular department. The advantage of this layout is flexibility. The disadvantage is inefficiency. Jobs or customers do not flow through the system in an orderly manner, backtracking is common, movement from department to department can take a considerable amount of time, and queues tend to develop. In addition, each new arrival may require that an operation be set up differently for its particular processing requirements. Although workers can operate a number of machines or perform a number of different tasks in a single department, their workload often fluctuates—from queues of jobs or customers waiting to be processed to idle time between jobs or customers. Figures 7.3 and 7.4 show schematic diagrams of process layouts in services and manufacturing.
Material storage and movement are directly affected by the type of layout. Storage space in a process layout is large to accommodate the large amount of in-process inventory. The factory may look like a warehouse, with work centers strewn between storage aisles. In-process inventory is high because material moves from work center to work center in batches waiting to be processed. Finished goods inventory, on the other hand, is low because the goods are being made for a particular customer and are shipped out to that customer on completion.
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Process layouts in manufacturing firms require flexible material handling equipment (such as forklifts, carts or AGVs) that can follow multiple paths, move in any direction, and carry large loads of in-process goods. A forklift moving pallets of material from work center to work center needs wide aisles to accommodate heavy loads and two-way movement. Scheduling of forklifts is typically controlled by radio dispatch and varies from day to day and hour to hour. Routes have to be determined and priorities given to different loads competing for pickup.
Figure 7.4 A Process Layout in Manufacturing
Process layouts in service firms require large aisles for customers to move back and forth and ample display space to accommodate different customer preferences.
The major layout concern for a process layout is where to locate the departments or machine centers in relation to each other. Although each job or customer potentially has a different route through the facility, some paths will be more common than others. Past information on customer orders and projections of customer orders can be used to develop patterns of flow through the shop.
PRODUCT LAYOUTS
Product layouts, better known as assembly lines, arrange activities in a line according to the sequence of operations that need to be performed to assemble a particular product. Each product has its own “line” specifically designed to meet its requirements. The flow of work is orderly and efficient, moving from one workstation to another down the assembly line until a finished product comes off the end of the line. Since the line is set up for one type of product or service, special machines can be purchased to match a product's specific processing requirements. Product layouts are suitable for mass production or repetitive operations in which demand is stable and volume is high. The product or service is a standard one made for a general market, not for a particular customer. Because of the high level of demand, product layouts are more automated than process layouts, and the role of the worker is different. Workers perform narrowly defined assembly tasks that do not demand as high a wage rate as those of the more versatile workers in a process layout.
Product layouts:
arrange activities in a line according to the sequence of operations for a particular product or service.
Process layouts are flexible; product layouts are efficient.
The advantage of the product layout is its efficiency and ease of use. The disadvantage is its inflexibility. Significant changes in product design may require that a new assembly line be built and new equipment be purchased. This is what happened to U.S. automakers when demand shifted to smaller cars. The factories that could efficiently produce six-cylinder engines could not be adapted to produce four-cylinder engines. A similar inflexibility occurs when demand volume slows. The fixed cost of a product layout (mostly for equipment) allocated over fewer units can send the price of a product soaring.
The major concern in a product layout is balancing the assembly line so that no one workstation becomes a bottleneck and holds up the flow of work through the line. Figure 7.5 shows the product flow in a product layout. Contrast this with the flow of products through the process layout shown in Figure 7.4.
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This photo shows a product layout where car bodies are moving down a paced assembly line with workers following along completing their tasks. Notice the workstations alongside the assembly line with tools, materials, signage, instructions, and andon lights (for signaling line slow down or stoppage). Today's factories are clean and orderly; inspectors even wear white gloves!
Figure 7.5 A Product Layout
A product layout needs material moved in one direction along the assembly line and always in the same pattern. Conveyors are the most common material handling equipment for product layouts. Conveyors can be paced (automatically set to control the speed of work) or unpaced (stopped and started by the workers according to their pace). Assembly work can be performed online (i.e., on the conveyor) or offline (at a workstation serviced by the conveyor).
Aisles are narrow because material is moved only one way, it is not moved very far, and the conveyor is an integral part of the assembly process, usually with workstations on either side. Scheduling of the conveyors, once they are installed, is simple—the only variable is how fast they should operate.
Storage space along an assembly line is quite small because in-process inventory is consumed in the assembly of the product as it moves down the assembly line. Finished goods, however, may require a separate warehouse for storage before they are shipped to dealers or stores to be sold.
Product and process layouts look different, use different material handling methods, and have different layout concerns. Table 7.1 summarizes the differences between product and process layouts.
Table 7.1 A Comparison of Product and Process Layouts
Product Layout
Process Layout
1. Description
Sequential arrangement of activities
Functional grouping of activities
2. Type of process
Continuous, mass production, mainly assembly
Intermittent, job shop, batch production, mainly fabrication
3. Product
Standardized, made to stock
Varied, made to order
4. Demand
Stable
Fluctuating
5. Volume
High
Low
6. Equipment
Special purpose
General purpose
7. Workers
Limited skills
Varied skills
8. Inventory
Low in-process, high finished goods
High in-process, low finished goods
9. Storage space
Small
Large
10. Material handling
Fixed path (conveyor)
Variable path (forklift)
11. Aisles
Narrow
Wide
12. Scheduling
Part of balancing
Dynamic
13. Layout decision
Line balancing
Machine location
14. Goal
Equalize work at each station
Minimize material handling cost
15. Advantage
Efficiency
Flexibility
Aircraft production generally takes place in a fixed position layout due to the size and complexity of assembly. Shown here is a Boeing 787 Dreamliner being outfitted.
FIXED-POSITION LAYOUTS
Fixed-position layouts are typical of projects in which the product produced is too fragile, bulky, or heavy to move. Ships, houses, and aircraft are examples. In this layout, the product remains stationary for the entire manufacturing cycle. Equipment, workers, materials, and other resources are brought to the production site. Equipment utilization is low because it is often less costly to leave equipment idle at a location where it will be needed again in a few days, than to move it back and forth. Frequently, the equipment is leased or subcontracted because it is used for limited periods of time. The workers called to the work site are highly skilled at performing the special tasks they are requested to do. For instance, pipefitters may be needed at one stage of production, and electricians or plumbers at another. The wage rate for these workers is much higher than minimum wage. Thus, if we were to look at the cost breakdown for fixed-position layouts, the fixed cost would be relatively low (equipment may not be owned by the company), whereas the variable costs would be high (due to high labor rates and the cost of leasing and moving equipment).
Fixed-position layouts:
are used for projects in which the product cannot be moved.
Fixed-position layouts are specialized to individual projects and thus are beyond the scope of this book. Projects are covered in more detail in the next chapter. In the sections that follow, we examine some quantitative approaches for designing product and process layouts.
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DESIGNING PROCESS LAYOUTS
Process layout objective: Minimize material handling costs.
In designing a process layout, we want to minimize movement or material handling cost, which is a function of the amount of material moved times the distance it is moved. This implies that departments that incur the most interdepartment movement should be located closest to each other, and those that do not interact should be located further away. Two techniques used to design process layouts, block diagramming and relationship diagramming, are based on logic and the visual representation of data.
BLOCK DIAGRAMMING
We begin with data on historical or predicted movement of material between departments in the existing or proposed facility. This information is typically provided in the form of a from/to chart, or load summary chart. The chart gives the average number of unit loads transported between the departments over a given period of time. A unit load can be a single unit, a pallet of material, a bin of material, or a crate of material—however material is normally moved from location to location. In automobile manufacturing, a single car represents a unit load. For a ballbearing producer, a unit load might consist of a bin of 100 or 1000 ball bearings, depending on their size.
ALONG THE SUPPLY CHAIN The Health Benefits of Good Layout
Steelcase furniture isn't just for offices anymore. Nurture, their line of patient-friendly furnishings, is part of an evidence-based design movement in healthcare where the impact of the physical environment on patient care and health is being investigated. Research shows that hospital design can cut infection rates, lower physician error, improve staff performance, shorten hospital stays, and save lives. The ideal patient room, for example, is a private room with three zones: (1) the patient zone, which includes the bed and overbed table; (2) the staff zone, with a sink, sanitizer, and counter for writing; and (3) the family zone, comfortable enough to encourage longer stays. Access is key to all areas—caregiver access to the patient, patient access to the bathroom, everyone's access to vital information. Rooms are designed as “acuity-adaptable,” meaning they can accommodate a variety of medical conditions. New rooms use more natural light, reduce noise, and improve infection control.
A hospital room in which the patient has ownership of his surroundings and feels connected to staff and loved ones is an environment exceptionally conducive to healing. The Center for Health Design estimates that such rooms can add $12 million to the cost of hospital construction, but with reduced falls and transfers, fewer infections, and safer care, those extra costs can be recouped within the first year of operation.
Courtesy Nurture by Steelcase, Inc.
Sources: Andrew Blum, “How Hospital Design Saves Lives,” Business***Week Online, August 15, 2006; Reena Jana, “Steelcase's Medical Breakthrough,” BusinessWeek, March 22, 2007; Chuck Salter, “A Prescription for Innovation,” Fast Company, April 2006; Nurture Web site, http://nurture.steelcase.com
The next step in designing the layout is to calculate the composite movements between departments and rank them from most movement to least movement. Composite movement, represented by a two-headed arrow, refers to the back-and-forth movement between each pair of departments.
Unit load:
the quantity in which material is normally moved
Finally, trial layouts are placed on a grid that graphically represents the relative distances between departments in the form of uniform blocks. The objective is to assign each department to a block on the grid so that nonadjacent loads are minimized. The term nonadjacent is defined as a distance farther than the next block, either horizontally, vertically, or diagonally. The trial layouts are scored on the basis of the number of nonadjacent loads. Ideally, the optimal layout would have zero nonadjacent loads. In practice, this is rarely possible, and the process of trying different layout configurations to reduce the number of nonadjacent loads continues until an acceptable layout is found.
Block diagramming tries to minimize nonadjacent loads.
Example 7.1 Process Layout
Barko, Inc. makes bark scalpers, processing equipment that strips the bark off trees and turns it into nuggets or mulch for gardens. The facility that makes bark scalpers is a small-job shop that employs 50 workers and is arranged into five departments: (1) bar stock cutting, (2) sheet metal, (3) machining, (4) painting, and (5) assembly. The average number of loads transported between the five departments per month is given in the accompanying load summary chart. The current layout of the facility is shown schematically on the 2 × 3 grid. Notice that there is quite a bit of flexibility in the facility, as indicated by the six possible locations (i.e., intersections) available for five departments. In addition, the forklift used in the facility is very flexible, allowing horizontal, vertical, and diagonal movement of material.
Barko management anticipates that a new bark scalper plant will soon be necessary and would like to know if a similar layout should be used or if a better layout can be designed. You are asked to evaluate the current layout in terms of nonadjacent loads, and if needed, propose a new layout on a 2 × 3 grid that will minimize the number of nonadjacent loads.
Solution
In order to evaluate the current layout, we need to calculate the composite, or back-and-forth, movements between departments. For example, the composite movement between department 1 and department 3 is the sum of 50 loads moved from 1 to 3, plus 60 loads moved from 3 to 1, or 110 loads of material. If we continue to calculate composite movements and rank them from highest to lowest, the following list results:
Composite
Movements
2↔3
200 loads
2 ↔ 4
150 loads
1 ↔ 3
110 loads
1 ↔ 2
100 loads
4 ↔ 5
60 loads
3 ↔ 5
50 loads
2 ↔ 5
50 loads
3 ↔ 4
40 loads
1 ↔ 4
0 loads
1 ↔ 5
0 loads
Next, we evaluate the “goodness” of the layout by scoring it in terms of nonadjacent loads. The results are shown visually in Grid 1.
The adjacent moves are marked with a solid line and the nonadjacent moves are shown with a curved dashed line to highlight the fact that material is moved farther than we would like, that is, across more than one square. Following our composite movement list, 2 ⇆ 3 and 2 ⇆ 4 are adjacent moves, but 1 ⇆ 3 is not. Our nonadjacent score starts with 110 loads of material from 1 ⇆ 3. Continuing down our list, all moves are adjacent and are marked with solid lines until 3 ⇆ 4. Movement 3 ⇆ 4 is nonadjacent, so we designate it as such and add 40 loads to our nonadjacent score. The remaining movements have zero loads. Thus, our score for this layout is 110 + 40 = 150 nonadjacent loads.
To improve the layout, we note that departments 3 and 4 should be located adjacent to department 2, and that departments 4 and 5 may be located away from department 1 without adding to the score of nonadjacent loads. Let's put departments 4 and 5 on one end of the grid and department 1 on the other and then fill in departments 2 and 3 in the middle. The revised solution is shown in Grid 2. The only nonadjacent moves are between departments 1 and 4, and 1 and 5. Since no loads of material are moved along those paths, the score for this layout is zero.
The Excel setup for this problem is shown in Exhibit 7.1.
The layout solution in Grid 2 represents the relative position of each department. The next step in the layout design is to add information about the space required for each department. Recommendations for workspace around machines can be requested from equipment vendors or found in safety regulations or operating manuals. In some cases, vendors provide templates of equipment layouts, with work areas included. Workspace allocations for workers can be specified as part of job design, recommended by professional groups, or agreed on through union negotiations. A block diagram can be created by “blocking in” the work areas around the departments on the grid. The final block diagram adjusts the block diagram for the desired or proposed shape of the building. Standard building shapes include rectangles, L shapes, T shapes, and U shapes.
Figure 7.6 a shows an initial block diagram for Example 7.1, and Figure 7.6 b shows a final block diagram. Notice that the space requirements vary considerably from department to department, but the relative location of departments has been retained from the grid.
Block diagram:
a type of schematic layout diagram that includes space requirements.
RELATIONSHIP DIAGRAMMING
The preceding solution procedure is appropriate for designing process layouts when quantitative data are available. However, in situations for which quantitative data are difficult to obtain or do not adequately address the layout problem, the load summary chart can be replaced with subjective input from analysts or managers. Richard Muther developed a format for displaying manager preferences for departmental locations, known as Muther's grid.2 The preference information is coded into six categories associated with the five vowels. A, E, I, O, and U, plus the letter X. As shown in Figure 7.7, the vowels match the first letter of the closeness rating for locating two departments next to each other. The diamond-shaped grid is read similarly to mileage charts on a road map. For example, reading down the highlighted row in Figure 7.7, it is okay if the offices are located next to production, absolutely necessary that the stockroom be located next to production, important that shipping and receiving be located next to production, especially important that the locker room be located next to production, and absolutely necessary that the toolroom be located next to production.
Muther's grid:
a format for displaying manager preferences for department locations.
The information from Muther's grid can be used to construct a relationship diagram that evaluates existing or proposed layouts. Consider the relationship diagram shown in Figure 7.8 a .
Relationship diagram:
a schematic diagram that uses weighted lines to denote location preference.
Exhibit 7.1 Using Excel for Process Layouts
A schematic diagram of the six departments from Figure 7.7 is given in a 2 × 3 grid. Lines of different thicknesses are drawn from department to department. The thickest lines (three, four, or five strands) identify the closeness ratings with the highest priority—that is, for which departments it is important, especially important, or absolutely necessary that they be located next to each other. The priority diminishes with line thickness. Undesirable closeness ratings are marked with a zigzagged line. Visually, the best solution would show short heavy lines and no zigzagged lines (undesirable locations are noted only if they are adjacent). Thin lines (one or two strands, representing unimportant or okay) can be of any length and for that reason are sometimes eliminated from the analysis. An alternative form of relationship diagramming uses colors instead of line thickness to visualize closeness ratings.
Manager preferences for department locations are displayed as A, E, I, O, U, or X.
Figure 7.6 Block Diagrams
From Figure 7.8 a , it is obvious that production and shipping and receiving are located too far from the stockroom and that the offices and locker room are located too close to one another. Figure 7.8 b shows a revised layout and evaluates the layout with a relationship diagram. The revised layout appears to satisfy the preferences expressed in Muther's grid. The heavy lines are short and within the perimeter of the grid. The lengthy lines are thin, and there are no zigzagged lines (X's are shown only if the departments are adjacent).
Figure 7.7 Muther's Grid
Figure 7.8 Relationship Diagrams
2 R. Muther, Systematic Layout Planning (Boston: Industrial Education Institute, 1961).
COMPUTERIZED LAYOUT SOLUTIONS
The diagrams just discussed help formulate ideas for the arrangement of departments in a process layout, but they can be cumbersome for large problems. Fortunately, several computer packages are available for designing process layouts. The best known are CRAFT (Computerized Relative Allocation of Facilities Technique) and CORELAP (Computerized Relationship Layout Planning). CRAFT takes a load summary chart and block diagram as input and then makes pairwise exchanges of departments until no improvements in cost or nonadjacency score can be found. The output is a revised block diagram after each iteration for a rectangular-shaped building, which may or may not be optimal. CRAFT is sensitive to the initial block diagram used; that is, different block diagrams as input will result in different layouts as outputs. For this reason, CRAFT is often used to improve on existing layouts or to enhance the best manual attempts at designing a layout.
CORELAP uses nonquantitative input and relationship diagramming to produce a feasible layout for up to 45 departments and different building shapes. It attempts to create an acceptable layout from the beginning by locating department pairs with A ratings first, then those with E ratings, and so on.
Simulation software for layout analysis, such as PROMODEL and EXTEND provide visual feedback and allow the user to quickly test a variety of scenarios. Three-D modeling and CAD-integrated layout analysis are available in VisFactory and similar software.
ALONG THE SUPPLY CHAIN Urban Outfitters' New Distribution Facility
In recessionary times, most businesses revise their growth strategies or change course. Not Urban Outfitters (UO). To support their goal of adding 500 new stores in North America, Europe, and Asia, UO decided to revamp their supply chain, build their own distribution center, and take control over logistics. Previously, a third party logistics (3PL) provider had handled shipping, warehousing, and distribution. To follow the logic of this decision, we'll start with the effects of the recession.
Lean times sometimes create unanticipated demand. Reducing the stock on shelves, a concept known as lean buying, can create a sense of urgency among customers so that they purchase now instead of waiting for markdowns. Lean buying also means smaller orders for suppliers and a supply chain that needs to be faster and more responsive.
One way to add flexibility to a supply chain is by dual sourcing. UO sources fabric and raw materials in alternate locations, allowing for shorter lead times in the event of a reorder. The smaller initial order (to test the waters) is sourced from one supplier, and the larger re-order is sourced from another suppler. Every two weeks, the UO supply chain team sits down with other key executives to evaluate and discuss sales and operations planning (see Chapter 14) and supply chain performance of its more than 1500 vendors.
A critical supply chain goal is to reduce the concept-to-market time from 18 weeks down to 9. (That's still a far cry from Zara's nine day design-to hanger time, but it's a start.) To begin the process, UO re-evaluated its Far East operations, the source of its private brand products. The upstream portion of the supply chain flows from designer, to raw materials merchant, to production planner, to production agent, to the factory. A bottleneck in the process has been the production agent, usually someone from the country of origin who facilitates communication and oversees production in the factory. UO has worked to more closely train these agents and, in some cases, to replace them with UO personnel. They are considering establishing a Hong Kong office to coordinate Far East production and consolidate global logistics functions.
In the states, Urban Outfitters has built a 175,500-square-foot distribution center PC) in Reno, Nevada. Although UO is based in Philadelphia, the West Coast DC location makes sense as most of the merchandise is imported from Asia. Taking over the logistics function from a third party provider allowed UO to further shorten the concept-to-market time. The DC uses a high-speed conveyor, sliding shoe sortation system, and pack-to-light technology. The facility handles on average 100,000 packages a day, but has shipped as many as 600,000 in a five-day week. Only 10% of the shipments into the center actually go into reserve storage for order fulfillment. Ninety percent are shipped directly to stores from inbound freight through a process known as cross-docking. Referring to the figure above, shipments arriving in the receiving area are entered into UO's enterprise resource planning (ERP) system (see Chapter 15) where merchandise is matched with store needs. Pallets are staged while cartons for each store are prepared and ticketed. As cases of goods arrive to the pack-to-light area, a packer scans the bar code label on a ticket in the lead case to launch the packing operation for that SKU. Lights on the pick racks identify which cartons, or stores, will get that SKU and how many cases or items should be placed in a carton. Once a shipping carton is full, it's pushed back onto the conveyor system. On its way to the shipping area it is weighed and taped, then routed to the appropriate truck for shipping to a UO store, without ever having entered storage.
In its first year of operation the new distribution center reduced operating costs per unit by 30% and turnaround time by 40%. The facility has room to expand to 429,000 square feet as the expansion strategy takes effect. Urban Outfitters has taken a holistic approach to design, sourcing, production, and distribution. Integrating facility decisions with strategy is an important step toward goal attainment.
1. What difference could in-house logistics versus 3PL make for a customer?
2. Why does cross docking make sense for Urban Outfitters?
3. Do you think UO's strategy of growth is sustainable? What might be the next area for expansion?
Sources: Dan McCue, “Urban Outfitters Sales into the Wind,” Inbound Logistics, September 2008; Bob Trebilcock, “Urban Outfitters' Against-the-Grain Distribution is Back In-house,” and “Distribution Redesign at Urban Outfitters,” Modern Materials Handling, April 1, 2008.
DESIGNING SERVICE LAYOUTS
Most service organizations use process layouts. This makes sense because of the variability in customer requests for service. Service layouts are designed in much the same way as process layouts in manufacturing firms, but the objectives may differ. For example, instead of minimizing the flow of materials through the system, services may seek to minimize the flow of paperwork or to maximize customer exposure to as many goods as possible. Grocery stores take this approach when they locate milk on one end of the store and bread on the other, forcing the customer to travel through aisles of merchandise that might prompt additional purchases.
Service layouts may have different objectives than manufacturing layouts.
In addition to the location of departments, service layouts are concerned with the circulation of customer traffic through the facility. There are a variety of ways to prompt the flow of customers through various processes or departments. You may have experienced a free-flow layout in The Disney Store, a grid layout in your grocery store, a spine layout in Barnes and Noble, or a circular layout in Kohl's department store. These layouts are shown in Figure 7.9. Free flow layouts encourage browsing, increase impulse purchasing, and are flexible and visually appealing. Grid layouts encourage customer familiarity, are low cost, easy to clean and secure, and good for repeat customers. Loop layouts and spine layouts fall between the extremes of free flow and grids. They both increase customer sightlines and exposure to products, while encouraging the customer to circulate through the entire store.3
Service layouts must be attractive as well as functional. In this photo, modular office units without permanent walls allow maximum flexibility, save space, and encourage communication.
Figure 7.9 Types of Store Layouts
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Service layouts are also concerned with the allocation of space to departments, the location of special displays, the efficiency of checkout procedures, and protection from pilferage. Space allocation is determined by evaluating the sales per square foot of a product or product line versus the willingness of a vendor to pay for product placement. Queuing analysis, discussed in Chapter 5, is a quantitative technique for improving waiting lines that often form at checkouts.
Industry-specific recommendations are available for layout and display decisions. Computerized versions, such as SLIM (Store Labor and Inventory Management) and COSMOS (Computerized Optimization and Simulation Modeling for Operating Supermarkets), consider shelf space, demand rates, profitability, and stockout probabilities in layout design.
Finally, services may have both a back office (invisible to the customer) and a front office (in full view of the customer) component. Back offices can be organized for efficiency and functionality, while front office layouts must be aesthetically pleasing as well as functional. For that reason, service layouts are often considered part of the service design process.
DESIGNING PRODUCT LAYOUTS
A product layout arranges machines or workers in a line according to the operations that need to be performed to assemble a particular product. From this description, it would seem the layout could be determined simply by following the order of assembly as contained in the bill of material for the product. To some extent, this is true. Precedence requirements, specifying which operations must precede others, which can be done concurrently and which must wait until later, are an important input to the product layout decision. But there are other factors that make the decision more complicated.
Product layout objective: Balance the assembly line.
Product layouts or assembly lines are used for high-volume production. To attain the required output rate as efficiently as possible, jobs are broken down into their smallest indivisible portions, called work elements. Work elements are so small that they cannot be performed by more than one worker or at more than one workstation. But it is common for one worker to perform several work elements as the product passes through his or her workstation. Part of the layout decision is concerned with grouping these work elements into workstations so products flow through the assembly line smoothly. A workstation is any area along the assembly line that requires at least one worker or one machine. If each workstation on the assembly line takes the same amount of time to perform the work elements that have been assigned, then products will move successively from workstation to workstation with no need for a product to wait or a worker to be idle. The process of equalizing the amount of work at each workstation is called line balancing.
Line balancing:
tries to equalize the amount of work at each workstation.
LINE BALANCING
Assembly-line balancing operates under two constraints: precedence requirements and cycle time restrictions.
Precedence requirements:
physical restrictions on the order in which operations are performed.
Precedence requirements are physical restrictions on the order in which operations are performed on the assembly line. For example, we would not ask a worker to package a product before all the components were attached, even if he or she had the time to do so before passing the product to the next worker on the line. To facilitate line balancing, precedence requirements are often expressed in the form of a precedence diagram. The precedence diagram is a network, with work elements represented by circles or nodes and precedence relationships represented by directed line segments connecting the nodes. We will construct a precedence diagram later in Example 7.2.
Cycle time, the other restriction on line balancing, refers to the maximum amount of time the product is allowed to spend at each workstation if the targeted production rate is to be reached.
Cycle time:
the maximum amount of time a product is allowed to spend at each workstation.
Desired cycle time is calculated by dividing the time available for production by the number of units scheduled to be produced:
Suppose a company wanted to produce 120 units in an 8-hour day. The cycle time necessary to achieve the production quota is
Cycle time can also be viewed as the time between completed items rolling off the assembly line. Consider the three-station assembly line shown here.
Cycle time is different from flow time.
It takes 12 minutes (i.e., 4 + 4 + 4) for each item to pass completely through all three stations of the assembly line. The time required to complete an item is referred to as its flow time. However, the assembly line does not work on only one item at a time. When fully operational, the line will be processing three items at a time, one at each workstation, in various stages of assembly. Every 4 minutes a new item enters the line at workstation 1, an item is passed from workstation 1 to workstation 2, another item is passed from workstation 2 to workstation 3, and a completed item leaves the assembly line. Thus, a completed item rolls off the assembly line every 4 minutes. This 4-minute interval is the actual cycle time of the line.
The actual cycle time, Ca, is the maximum workstation time on the line. It differs from the desired cycle time when the production quota does not match the maximum output attainable by the system. Sometimes the production quota cannot be achieved because the time required for one work element is too large. To correct the situation, the quota can be revised downward or parallel stations can be set up for the bottleneck element.
Line balancing is basically a trial-and-error process. We group elements into workstations recognizing time and precedence constraints. For simple problems, we can evaluate all feasible groupings of elements. For more complicated problems, we need to know when to stop trying different workstation configurations. The efficiency of the line can provide one type of guideline; the theoretical minimum number of workstations provides another. The formulas for efficiency, E, and minimum number of workstations, N, are
Actual cycle time is the result from the balancing procedure.
Calculate line efficiency and the theoretical minimum number of workstations.
where
ti = completion time for element i
j = number of work elements
n = actual number of workstations
Ca = actual cycle time
Cd = desired cycle time
Balance delay:
the total idle time of the line.
The total idle time of the line, called balance delay, is calculated as (1 - efficiency). Efficiency and balance delay are usually expressed as percentages. In practice, it may be difficult to attain the theoretical number of workstations or 100% efficiency.
Line balancing groups elements into workstations.
The line balancing process can be summarized as follows:
1. Draw and label a precedence diagram.
2. Calculate the desired cycle time required for the line.
3. Calculate the theoretical minimum number of workstations.
4. Group elements into workstations, recognizing cycle time and precedence constraints.
5. Calculate the efficiency of the line.
6. Determine if the theoretical minimum number of workstations or an acceptable efficiency level has been reached. If not, go back to step 4.
Example 7.2 Line Balancing
Real Fruit Snack Strips are made from a mixture of dried fruit, food coloring, preservatives, and glucose. The mixture is pressed out into a thin sheet, imprinted with various shapes, rolled, and packaged. The precedence and time requirements for each step in the assembly process are given below. To meet demand, Real Fruit needs to produce 6000 fruit strips every 40-hour week. Design an assembly line with the fewest number of workstations that will achieve the production quota without violating precedence constraints.
Work Element
Precedence
Time (min)
A
Press out sheet of fruit
—
0.1
B
Cut into strips
A
0.2
C
Outline fun shapes
A
0.4
D
Roll up and package
B,C
0.3
Solution
First, we draw the precedence diagram as follows.
The precedence diagram is completed by adding the time requirements beside each node. Next, we calculate the desired cycle time and the theoretical minimum number of workstations:
To balance the line, we must group elements into workstations so that the sum of the element times at each workstation is less than or equal to the desired cycle time of 0.4 minute. Examining the precedence diagram, we begin with A since it is the only element that does not have a precedence. We assign A to workstation 1. B and C are now available for assignment. Cycle time is exceeded with A and C in the same workstation, so we assign B to workstation 1 and place C in a second workstation. No other element can be added to workstation 2, due to cycle time constraints. That leaves D for assignment to a third workstation. Elements grouped into workstations are circled on the precedence diagram and placed into workstations shown on the assembly line diagram.
Workstation
Element
Remaining Time
Remaining Elements
1
A
0.3
B,C
B
0.1
C,D
2
C
0.0
D
3
D
0.1
none
Assembly-line diagram:
Since the theoretical minimum number of workstations was three, we know we have balanced the line as efficiently as possible. The assembly line has an efficiency of
3 The material in this section is adapted from Patrick Dunne, Robert Lusch, and David Griffith, Retailing, 4th ed. (Southwestern College Publishing, 2001).
COMPUTERIZED LINE BALANCING
Line balancing by hand becomes unwieldy as the problems grow in size. Fortunately, there are software packages that will balance large lines quickly. IBM's COMSOAL (Computer Method for Sequencing Operations for Assembly Lines) and GE's ASYBL (Assembly Line Configuration Program) can assign hundreds of work elements to workstations on an assembly line. These programs, and most that are commercially available, do not guarantee optimal solutions. They use various heuristics, or rules, to balance the line at an acceptable level of efficiency. Five common heuristics are: longest operation time, shortest operation time, most number of following tasks, least number of following tasks, and ranked positional weight. Positional weights are calculated by summing the processing times of those tasks that follow an element. These heuristics specify the order in which work elements are considered for allocation to workstations. Elements are assigned to workstations in the order given until the cycle time is reached or until all tasks have been assigned. The most number of following tasks heuristic was used in Example 7.2.
Line-balancing heuristics specify the order in which work elements are allocated to workstations.
HYBRID LAYOUTS
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Hybrid layouts modify and/or combine some aspects of product and process layouts. We discuss three hybrid layouts: cellular layouts, flexible manufacturing systems, and mixed-model assembly lines.
CELLULAR LAYOUTS
Cellular layouts attempt to combine the flexibility of a process layout with the efficiency of a product layout. Based on the concept of group technology (GT), dissimilar machines or activities are grouped into work centers, called cells, to process families of parts or customers with similar requirements. (Figure 7.10 shows a family of parts with similar shapes, and a family of related grocery items.) The cells are arranged in relation to each other so that material movement is minimized. Large machines that cannot be split among cells are located near to the cells that use them, that is, at their point of use.
Cellular layouts:
group dissimilar machines into work centers (called cells) that process families of parts with similar shapes or processing requirements.
The layout of machines within each cell resembles a small assembly line. Thus, line-balancing procedures, with some adjustment, can be used to arrange the machines within the cell. The layout between cells is a process layout. Therefore, computer programs such as CRAFT can be used to locate cells and any leftover equipment in the facility.
Production flow analysis:
reorders part routing matrices to identify families of parts with similar processing requirements.
Consider the process layout in Figure 7.11. Machines are grouped by function into four distinct departments. Component parts manufactured in the process layout section of the factory are later assembled into a finished product on the assembly line. The parts follow different flow paths through the shop. Three representative routings, for parts A, B, and C, are shown in the figure. Notice the distance that each part must travel before completion and the irregularity of the part routings. A considerable amount of “paperwork” is needed to direct the flow of each individual part and to confirm that the right operation has been performed. Workers are skilled at operating the types of machines within a single department and typically can operate more than one machine at a time.
Figure 7.10 Group Technology (a) A family of similar parts. (b) A family of related grocery items.
Source: Adapted from Mikell P. Groover, Automation, Production Systems, and Computer Integrated Manufacturing © 1987. Adapted by permission of Pearson Education, Inc., Upper Saddle River, NJ.
Figure 7.11 Original Process Layout with Routing Matrix
Figure 7.11 gives the complete part routing matrix for the eight parts processed through the facility. In its current form, there is no apparent pattern to the routings. Production flow analysis (PFA) is a group technology technique that reorders part routing matrices to identify families of parts with similar processing requirements. The reordering process can be as simple as using the “Data Sort” command in Excel for the most common machines, or as sophisticated as pattern-recognition algorithms from the field of artificial intelligence. Figure 7.12 shows the results of reordering. Now the part families and cell formations are clear. Cell 1, consisting of machines 1, 2, 4, 8, and 10, will process parts A, D, and F: Cell 2, consisting of machines 3, 6, and 9, will process products C and G; and Cell 3, consisting of machines 5, 7, 11, and 12, will process parts B, H, and E. A complete cellular layout showing the three cells feeding a final assembly line is also given in Figure 7.12. The representative part flows for parts A, B, and C are much more direct than those in the process layout. There is no backtracking or crisscrossing of routes, and the parts travel a shorter distance to be processed. Notice that parts G and E cannot be completely processed within cells 2 and 3. to which they have been assigned. However, the two cells are located in such a fashion that the transfer of parts between the cells does not involve much extra movement.
The U shape of cells 1 and 3 is a popular arrangement for manufacturing cells because it facilitates the rotation of workers among several machines. Workers in a cellular layout typically operate more than one machine, as was true of the process layout. However, workers who are assigned to each cell must now be multifunctional—that is, skilled at operating many different kinds of machines, not just one type, as in the process layout. In addition, workers are assigned a path to follow among the machines that they operate, which may or may not coincide with the path the product follows through the cell. Figure 7.13 shows a U-shaped manufacturing cell including worker paths.
Figure 7.12 Revised Cellular Layout with Reordered Routing Matrix
Figure 7.13 A Manufacturing Cell with Worker Paths
Source: J.T. Black, “Cellular Manufacturing Systems Reduce Setup Time, Make Small Lot Production Economical.” Industrial Engineering (November 1983). Reprinted with the permission of the Institute of Industrial Engineers, 3577 Parkway Lane, Suite 200, Norcross, GA 30092, 770-449-0461 © 1983.
Advantages of Cellular Layouts
Cellular layouts have become popular in the past decade as the backbone of modern factories. Cells can differ considerably in size, in automation, and in the variety of parts processed. As small interconnected layout units, cells are common in services, as well as manufacturing.
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Cellular layouts reduce transit time, setup time, and in-process inventory.
The advantages of cellular layouts are as follows:
• Reduced material handling and transit time . Material movement is more direct. Less distance is traveled between operations. Material does not accumulate or wait long periods of time to be moved. Within a cell, the worker is more likely to carry a partially finished item from machine to machine than wait for material-handling equipment, as is characteristic of process layouts where larger loads must be moved farther distances.
• Reduced setup time. Since similar parts are processed together, the adjustments required to set up a machine should not be that different from item to item. If it does not take that long to change over from one item to another, then the changeover can occur more frequently, and items can be produced and transferred in very small batches or lot sizes.
• Reduced work-in-process inventory. In a work cell, as with assembly lines, the flow of work is balanced so that no bottleneck or significant buildup of material occurs between stations or machines. Less space is required for storage of in-process inventory between machines, and machines can be moved closer together, thereby saving transit time and increasing communication.
• Better use of human resources. Typically, a cell contains a small number of workers responsible for producing a completed part or product. The workers act as a self-managed team, in most cases more satisfied with the work that they do and more particular about the quality of their work. Labor in cellular manufacturing is a flexible resource. Workers in each cell are multifunctional and can be assigned to different routes within a cell or between cells as demand volume changes.
• Easier to control . Items in the same part family are processed in a similar manner through the work cell. There is a significant reduction in the paperwork necessary to document material travel, such as where an item should be routed next, if the right operation has been performed, and the current status of a job. With fewer jobs processed through a cell, smaller batch sizes, and less distance to travel between operations, the progress of a job can be verified visually rather than by mounds of paperwork.
• Easier to automate . Automation is expensive. Rarely can a company afford to automate an entire factory all at once. Cellular layouts can be automated one cell at a time. Figure 7.14 shows an automated cell with one robot in the center to load and unload material from several CNC machines and an incoming and outgoing conveyor. Automating a few workstations on an assembly line will make it difficult to balance the line and achieve the increases in productivity expected. Introducing automated equipment in a job shop has similar results, because the “islands of automation” speed up only certain processes and are not integrated into the complete processing of a part or product.
Disadvantages of Cellular Layouts
In spite of their many advantages, cellular layouts are not appropriate for all types of businesses. The following disadvantages of cellular layouts must be considered:
• Inadequate part families . There must be enough similarity in the types of items processed to form distinct part families. Cellular manufacturing is appropriate for medium levels of product variety and volume. The formation of part families and the allocation of machines to cells is not always an easy task. Part families identified for design purposes may not be appropriate for manufacturing purposes.
Cellular layouts require distinct part families, careful balancing, expanded worker training, and increased capital investment.
Figure 7.14 An Automated Manufacturing Cell
Source: J. T. Black, “Cellular Manufacturing Systems Reduce Setup Time, Make Small Lot Production Economical.” Industrial Engineering (November 1983). Reprinted with the permission of the Institute of Industrial Engineers, 3577 Parkway Lane, Suite 200, Norcross, GA 30092, 770-449-0461, © 1983.
• Poorly balanced cells. Balancing the flow of work through a cell is more difficult than assembly-line balancing because items may follow different sequences through the cell that require different machines or processing times. The sequence in which parts are processed can thus affect the length of time a worker spends at a certain stage of processing and thus delay his arrival to a subsequent stage in his worker path. Poorly balanced cells can be very inefficient. It is also important to balance the workload among cells in the system, so that one cell is not overloaded while others are idle. This may be taken care of in the initial cellular layout, only to become a problem as changes occur in product designs or product mix. Severe imbalances may require the reformation of cells around different part families, and the cost and disruption that implies.
• Expanded training and scheduling of workers. Training workers to do different tasks is expensive and time-consuming and requires the workers' cooperation. Some tasks are too different for certain workers to master. Although flexibility in worker assignment is one of the advantages of cellular layouts, the task of determining and adjusting worker paths within or between cells can be quite complex.
• Increased capital investment. In cellular manufacturing, multiple smaller machines are preferable to single large machines. Implementing a cellular layout can be economical if new machines are being purchased for a new facility, but it can be quite expensive and disruptive in existing production facilities where new layouts are required. Existing equipment may be too large to fit into cells or may be underutilized when placed in a single cell. Additional machines of the same type may have to be purchased for different cells. The cost and downtime required to move machines can also be high.
FLEXIBLE MANUFACTURING SYSTEMS
A flexible manufacturing system (FMS) consists of numerous programmable machine tools connected by an automated material handling system and controlled by a common computer network. It is different from traditional automation, which is fixed or “hard wired” for a specific task. Fixed automation is very efficient and can produce in very high volumes, but is not flexible. Only one type or model of product can be produced on most automated production lines, and a change in product design would require extensive changes in the line and its equipment.
Flexible manufacturing system:
can produce an enormous variety of items.
An FMS combines flexibility with efficiency. Tools change automatically from large storage carousels at each machine, which hold hundreds of tools. The material-handling system (usually conveyors or automated guided vehicles) carries workpieces on pallets, which can be locked into a machine for processing. Pallets are transferred between the conveyor and machine automatically. Computer software keeps track of the routing and processing requirements for each pallet. Pallets communicate with the computer controller by way of bar codes or radio signals. Parts can be transferred between any two machines in any routing sequence. With a variety of programmable machine tools and large tool banks, an FMS can theoretically produce thousands of different items as efficiently as a thousand of the same item.
The efficiency of an FMS is derived from reductions in setup and queue times. Setup activities take place before the part reaches the machine. A machine is presented only with parts and tools ready for immediate processing. Queuing areas at each machine hold pallets ready to move in the moment the machine finishes with the previous piece. The pallet also serves as a work platform, so no time is lost transferring the workpiece from pallet to machine or positioning and fixturing the part. The machines in an advanced FMS, such as five-axis CNC machining centers, simultaneously perform up to five operations on a workpiece that would normally require a series of operations on individual machines.
FMS layouts differ based on the variety of parts that the system can process, the size of the parts processed, and the average processing time required for part completion. Figure 7.15 shows a simple FMS where parts rotate on a conveyor until a machine is available for processing.
MIXED-MODEL ASSEMBLY LINES
Traditional assembly lines, designed to process a single model or type of product, can be used to process more than one type of product but not efficiently. Models of the same type are produced in long production runs, sometimes lasting for months, and then the line is shut down and changed over for the next model. The next model is also run for an extended time, producing perhaps half a year to a year's supply; then the line is shut down again and changed over for yet another model; and so on. The problem with this arrangement is the difficulty in responding to changes in customer demand. If a certain model is selling well and customers want more of it, they have to wait until the next batch of that model is scheduled to be produced. On the other hand, if demand is disappointing for models that have already been produced, the manufacturer is stuck with unwanted inventory.
Recognizing that this mismatch of production and demand is a problem, some manufacturers concentrated on devising more sophisticated forecasting techniques. Others changed the manner in which the assembly line was laid out and operated so that it really became a mixed-model assembly line. First, they reduced the time needed to change over the line to produce different models. Then they trained their workers to perform a variety of tasks and allowed them to work at more than one workstation on the line, as needed. Finally, they changed the way in which the line was arranged and scheduled. The following factors are important in the design and operation of mixed-model assembly lines.
Figure 7.15 A Flexible Manufacturing System
Mixed-model assembly line:
processes more than one product model.
Single-model and mixed-model assembly lines differ in layout and operation.
• Line balancing . In a mixed-model line, the time to complete a task can vary from model to model. Instead of using the completion times from one model to balance the line, a distribution of possible completion times from the array of models must be considered. In most cases, the expected value, or average, times are used in the balancing procedure. Otherwise, mixed-model lines are balanced in much the same way as single-model lines.
• U-shaped lines . To compensate for the different work requirements of assembling different models, it is necessary to have a flexible workforce and to arrange the line so that workers can assist one another as needed. Figure 7.16 shows how the efficiency of an assembly line can be improved when a U-shaped line is used.
• Flexible workforce . Although worker paths are predetermined to fit within a set cycle time, the use of average time values in mixed-model lines will produce variations in worker performance. Hence, the flexibility of workers helping other workers makes a tremendous difference in the ability of the line to adapt to the varied length of tasks inherent in a mixed-model line.
• Model sequencing . Since different models are produced on the same line, mixed-model scheduling involves an additional decision—the order, or sequence, of models to be run through the line. From a logical standpoint, it would be unwise to sequence two models back to back that require extra long processing times. It would make more sense to mix the assembling of models so that a short model (requiring less than the average time) followed a long one (requiring more than the average time). With this pattern, workers could “catch up” from one model to the next.
Figure 7.16 Balancing U-Shaped Lines
Another objective in model sequencing is to spread out the production of different models as evenly as possible throughout the time period scheduled. This concept of uniform production will be discussed in Chapter 16, “Lean Production.”
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SUMMARY
Capacity planning is the process of establishing the overall level of productive resources for a firm. It involves long-term strategic activities, such as the acquisition of new facilities, technologies, or businesses, that take a year or more to complete.
Capacity expansion can lead demand, lag behind demand, or meet average demand. The best operating level for a facility often includes a capacity cushion for unexpected occurrences. The tendency of high levels of output to cost less per unit is known as economies of scale. This normally holds true up to a certain level of output, at which point diseconomies of scale can take over.
Facility decisions are an important part of operations strategy. An effective layout reflects a firm's competitive priorities and enables the firm to reach its strategic objectives. Batch production, which emphasizes flexibility, is most often organized into a process layout, whereas mass production uses a product layout for maximum efficiency. Because of their size and scope, projects tend to use fixed-position layouts. Service layouts may try to process customers through the system as quickly as possible or maximize customer exposure to products and services.
In the current manufacturing environment of new product introductions, rapidly changing technologies, and intense competition, the ability of a manufacturing system to adapt is essential. Thus, several hybrid layouts have emerged that combine flexibility and efficiency. Reductions in setup times have made mixed-model assembly lines feasible. The newest flexible manufacturing systems (FMSs) can process any item that fits the dimensions of the pallet on which it is transported. Manufacturing cells that resemble small assembly lines are designed to process families of items. Some companies are placing wheels and casters on their machines so that the cells can be adjusted as needed. Others are experimenting with modular conveyor systems that allow assembly lines to be rearranged while workers are on their lunch break.
As important as flexibility is, the cost of moving material is still a primary consideration in layout design. Today, as in the past, layout decisions are concerned with minimizing material flow. However, with reduced inventory levels, the emphasis has shifted from minimizing the number of loads moved to minimizing the distance they are moved. Instead of accumulating larger loads of material and moving them less often, machines are located closer together to allow the frequent movement of smaller loads. Planners who used to devote a considerable amount of time to designing the location of storage areas and the movement of material into and out of storage areas are now concerned with the rapid movement of material to and from the facility itself. The logistics of material transportation is discussed in Chapter 10, “Supply Chain Management.”
SUMMARY OF KEY FORMULAS
Desired Cycle Time
Actual Cycle Time
Ca = maximum workstation time
Theoretical Minimum Number of Workstations
Efficiency
Balance Delay
1 – efficiency
SUMMARY OF KEY TERMS
balance delay the total idle time of an assembly line.
best operating level the percent of capacity utilization at which unit costs are lowest.
block diagram a schematic layout diagram that includes the size of each work area.
capacity the maximum capability to produce.
capacity cushion a percent of capacity held in reserve for unexpected occurrences.
capacity planning a long-term strategic decision that establishes the overall level of productive resources for a firm.
cellular layout a layout that creates individual cells to process parts or customers with similar requirements.
cycle time the maximum amount of time an item is allowed to spend at each workstation if the targeted production rate is to be achieved; also, the time between successive product completions.
diseconomies of scale when higher levels of output cost more per unit to produce.
economies of scale when it costs less per unit to produce higher levels of output.
facility layout the arrangement of machines, departments, workstations, and other areas within a facility.
fixed-position layout a layout in which the product remains at a stationary site for the entire manufacturing cycle.
flexible manufacturing system (FMS) programmable equipment connected by an automated material-handling system and controlled by a central computer.
line balancing a layout technique that attempts to equalize the amount of work assigned to each workstation on an assembly line.
mixed-model assembly line an assembly line that processes more than one product model.
Muther's grid a format for displaying manager preferences for department locations.
precedence requirements physical restrictions on the order in which operations are performed.
process layout a layout that groups similar activities together into work centers according to the process or function they perform.
product layout a layout that arranges activities in a line according to the sequence of operations that are needed to assemble a particular product.
production flow analysis (PFA) a group technology technique that reorders part routing matrices to identify families of parts with similar processing requirements.
relationship diagram a schematic diagram that denotes location preference with different line thicknesses.
unit load the quantity in which material is normally moved, such as a unit at a time, a pallet, or a bin of material.
SOLVED PROBLEMS
• Animated Demo Problem
1. PROCESS LAYOUT
Mohawk Valley Furniture Warehouse has purchased a retail outlet with six departments, as shown below. The anticipated number of customers that move between the departments each week is given in the load summary chart.
a. Calculate the nonadjacent loads for the layout shown below.
b. Revise Mohawk's layout such that nonadjacent loads are minimized.
DEPARTMENT
A
B
C
D
E
F
A
—
70
50
B
—
100
C
70
—
D
80
—
E
40
—
30
F
60
100
—
SOLUTION
Composite movements ranked from highest to lowest are as follows:
E↔F
130
B↔C
70
B↔E
100
B↔F
60
C↔D
80
A↔F
50
A↔B
70
A↔E
40
a.
b.
2. PRODUCT LAYOUT
The Basic Block Company needs to produce 4000 boxes of blocks per 40-hour week to meet upcoming holiday demand. The process of making blocks can be broken down into six work elements. The precedence and time requirements for each element are as follows. Draw and label a precedence diagram for the production process. Set up a balanced assembly line and calculate the efficiency of the line.
WORK ELEMENT
PRECEDENCE
PERFORMANCE TIME (MIN)
A
—
0.10
B
A
0.40
C
A
0.50
D
—
0.20
E
C,D
0.60
F
B,E
0.40
SOLUTION
Start at the beginning of the network and group elements into workstations until cycle time has been reached. Do not violate precedence requirements.
• Internet Exercises
QUESTIONS
7-1. Why is capacity planning strategically important?
7-2. Describe three strategies for expanding capacity. What are the advantages and disadvantages of incremental versus one-step expansion?
7-3. Explain economies and diseconomies of scale. Give an example of each.
7-4. Explore capacity planning at your university or place of business. How is capacity measured? What factors influence the acquisition and allocation of resources?
7-5. Look around your classroom. Which layout characteristics help the learning process, and which ones hinder it? How does layout affect the manner in which the class is taught?
7-6. Visit a local McDonald's, Burger King, and Taco Bell (or similar establishments). How do their layouts differ? Which appears to be most efficient? Why?
7-7. Does layout make a difference? Think of a time when the layout of a facility impeded a process with which you were involved. Think of a time when a layout made it easier for a process to be completed.
7-8. List five goals of facility layout. Give an example of a facility you know that emphasizes each goal.
7-9. Distinguish between a process and product layout. Give an example of each.
7-10. Give an example of a fixed-position layout for producing a product and providing a service.
7-11. What type of layout(s) would be appropriate for:
a. A grocery store?
b. Home construction?
c. Electronics assembly?
d. A university?
7-12. What are the fixed and variable cost tradeoffs among product, process, and fixed-position layouts? Draw a cost/volume graph to illustrate your answer.
7-13. What is the difference between block diagramming and relationship diagramming? When might each be used?
7-14. How do service layouts differ from manufacturing layouts? Give an example of a well-designed service layout and an example of a poorly designed layout.
7-15. What are the objectives of line balancing? Describe several heuristic approaches to line balancing.
7-16. How are manufacturing cells formed? How does the role of the worker differ in cellular manufacturing?
7-17. Discuss the advantages and disadvantages of cellular layouts. How does a cellular layout combine a product and process layout?
7-18. Describe a flexible manufacturing system. How does it differ from a cellular layout?
7-19. How do mixed-model assembly lines differ from traditional assembly lines? What additional decisions are required?
7-20. Look for layout software packages on the Internet. What do systems like VisFactory do? Can you find any of the layout approaches discussed in the text?
7-21. Find a virtual plant tour on the Internet and describe the production system according to the criteria in Table 7.1.
7-22. Even better than virtual tours are actual tours. Take a tour of two production or distribution facilities in your area. Look for the basic and hybrid layouts discussed in this chapter. Also, look for bottlenecks and smooth flow. Write a paper comparing the two layouts.
• GO Tutorial
PROBLEMS
7-1. Maureen Marcy is designing the layout for a new business in town. The Collegiate Spa. From visiting spas in neighboring towns, she has compiled the following data on movement between spa activities. Help Maureen determine where to locate each activity on a 2 × 3 grid so that nonadjacent moves are minimized.
1
2
3
4
5
6
1 - Relaxation Lounge
50
25
75
2 - Facial
10
75
3 - Massage
30
50
50
4 - Power Shower
25
5 - Mineral Bath
50
50
6 - Sauna
7-2. Spiffy Dry Cleaners has recently changed management, and the new owners want to revise the current layout. The store performs six main services: (1) laundry, (2) dry cleaning, (3) pressing, (4) alterations, (5) delivery, and (6) tuxedo rental. Each is located in a separate department, as shown here. The load summary chart gives the current level of interaction between the departments. Calculate the number of nonadjacent loads for the current layout. Design an alternative layout to minimize the number of nonadjacent loads.
Load Summary Chart
1
2
3
4
5
6
1
—
125
40
2
—
45
75
3
—
20
235
200
4
60
30
10
—
85
50
5
—
10
6
40
30
150
—
7-3 Given the following load summary chart, design a layout on a 2 × 3 grid that will minimize nonadjacent loads.
Load Summary Chart
From/To
1
2
3
4
5
1
—
50
25
2
—
20
100
3
30
10
—
75
4
40
—
5
60
—
7-4. Pratt's Department Store is opening a new store in The Center's Mall. Customer movement tracked in its existing stores is shown below. Design a layout for Pratt's new store on a 2 × 3 grid that will minimize nonadjacent customer movement.
Number of Customers
From/To
Women's
Men's
Boys'
Girls'
Infants
Housewares
Women's
—
20
50
50
50
70
Men's
—
20
10
20
Boys'
20
—
20
Girls'
30
50
—
30
Infants
30
—
Housewares
40
—
7-5. Rent With Us Management Inc. has purchased a large housing complex and must decide where to locate its offices and service facilities. The company has learned that locating each service in a different apartment building helps control the behavior of tenants, but it would also like to keep unnecessary transit time to a minimum. Data collected on movements between facilities during a six month period from a similar apartment complex are shown below. Construct a layout diagram on a 2 × 3 grid that minimizes nonadjacent movement.
Site to Site Travel
From/To
Management
Rent Collection
Sales
Grounds
Maintenance
1. Management
—
20
35
25
20
2. Rent collection
50
—
35
3. Sales
40
—
10
4. Grounds
20
—
40
5. Maintenance
20
10
50
—
7-6. Avalanche, Inc. is a manufacturer of premium snow skis. The work is a combination of precision machining and skilled craftsmanship. Before completion, skis are processed back and forth between six different departments: (1) molding, (2) cutting, (3) fiberglass weaving, (4) gluing, (5) finishing, and (6) waxing. Avalanche is opening a new production facility and wants to lay it out as efficiently as possible. The number of loads of material moved from department to department at existing operations in other plants is shown below. Arrange the department for Avalanche's new plant in a 2 × 3 grid so that nonadjacent loads are minimized.
Load Summary Chart To
From
1
2
3
4
5
6
1
—
100
75
100
60
2
10
—
45
60
3
30
—
85
4
100
50
—
70
5
25
70
30
40
—
65
6
65
35
—
7-7. Marillion Hospital is building a satellite clinic in the Cold Harbor area of Richmond. The design committee has collected data on patient movement from similar facilities in hopes of making the new facility more efficient and customer-friendly.
Patient Movements To
From
1
2
3
4
5
6
1 Intake
—
50
10
25
10
100
2 Exam room
—
30
40
20
20
3 Radiology
40
—
20
60
40
4 Laboratory
10
10
—
10
40
5 Orthopedics
30
20
10
—
30
6 Waiting room
40
60
50
20
50
—
a. Calculate the nonadjacent loads for the initial layout.
b. Which pairwise exchange of departments would most improve the layout?
7-8. Social Services is moving into a new facility. Historical data on client visitation per month among its six departments is shown below. Design a layout for the new facility on a 2 × 3 grid that minimizes the distance clients must travel to receive services.
To
From
1
2
3
4
5
6
1
—
140
100
2
—
200
3
100
—
4
80
—
5
70
—
60
6
60
100
—
7-9. Tech Express provides technical assistance to customers through six separate departments. While much of the communication is electronic, it is helpful for departments working together on a customer's request to be physically located near to each other. Given the following data on customer “flow” between departments, design a layout on a 2 × 3 grid that will facilitate the maximum collaboration among departments. How much customer flow is nonadjacent?
Customer Flow To
From
1
2
3
4
5
6
1
—
50
100
25
60
2
40
—
80
150
3
10
70
—
55
4
10
80
—
5
40
80
—
30
6
60
50
—
7-10. Flying Flags is opening a new theme park in southern Indiana. The park will have six main attractions: (a) animal kingdom, (b) Broadway shows, (c) carousel and other kiddie rides, (d) daredevil roller coasters, (e) eating places, (f) flying machines, and (g) games. Data on customer flow patterns from similar parks is shown here, along with the layout for a similar park in Virginia. Calculate the nonadjacent loads for the Virginia park; then improve the design for the new Indiana location.
From/To
1
2
3
4
5
6
1
—
20
100
10
10
20
2
—
30
50
3
20
—
4
50
—
50
300
5
30
50
60
40
—
50
6
10
200
60
—
7-11. Design a layout on a 2 × 3 grid that satisfies the preferences listed here.
7-12. Design a layout on a 2 × 3 grid that satisfies these preferences.
7-13. Amber Ale use a simple five-step process to prepare its products for shipment. Because of recent increases in demand, the company is setting up an assembly line to do the work. How should the line be constructed if Amber needs a new product off the line every 10 minutes? Draw a precedence diagram, group the tasks into workstations, determine the efficiency of the line, and calculate the expected output for an eight-hour day. (There are multiple solutions to this problem.)
Task
Precedence
Time (mins)
A
None
5
B
A
2
C
A
4
D
A
7
E
B,C,D
5
7-14. The Henry Street Mission uses volunteers to assemble care packages for needy families during the holiday season. The mission would like to organize the work as efficiently as possible. A list of tasks, task times, and precedence requirements follows:
Task
Precedence
Time (mins)
A
—
6
B
A
3
C
B
7
D
B
5
E
C,D
4
F
E
5
a. If the mission wants to complete a care package every 10 minutes, how many volunteers should be called in? Balance the line and calculate the efficiency. How many packages can be assembled in a four-hour period?
b. Suppose that volunteers are plentiful. Balance the line to maximize output. What is the efficiency of the line? How many care packages can be assembled in a four-hour period?
7-15. Best Vision is revamping its assembly lines to improve efficiency. As shown below, there are 10 steps to assembling a television set.
a If Best needs to produce 120 televisions in a 40-hour work week, how should the line be balanced? Given that one worker is assigned to each workstation, how many workers are required to operate the line? What is the efficiency of the line?
b If demand for televisions is reduced to 100 sets per 40-hour week, how many workers will be needed to man the line? Re-balance the line and re-calculate its efficiency.
Task
Precedence
Time (min)
A
None
8
B
A
4
C
A
7
D
A
3
E
B
7
F
C,E
11
G
D
2
H
G
8
I
F,H
5
J
I
7
7-16. Professional Image Briefcases is an exclusive producer of handcrafted, stylish cases. The company assembles each case with care and attention to detail. This laborious process requires the completion of the six primary work elements listed here.
Work Element
Precedence
Time (min)
A
Tan leather
—
30
B
Dye leather
A
15
C
Shape case
B
10
D
Mold hinges and fixtures
—
5
E
Install hinges and fixtures
C,D
10
F
Assemble case
E
10
a. Construct a precedence diagram for the manufacturing of briefcases.
b. Compute the flow time required for assembling one briefcase and the cycle time necessary to assemble 50 cases in a 40-hour week.
c. Balance the line and compute its efficiency.
d. How would you change the line to produce 80 cases per week?
7-17. The TLB Yogurt Company must be able to make 600 party cakes in a 40-hour week. Use the following information to draw and label a precedence diagram, compute cycle time, compute the theoretical minimum number of workstations, balance the assembly line, and calculate its efficiency.
Work Element
Precedence
Performance Time (min)
A
—
1
B
A
2
C
B
2
D
A, E
4
E
—
3
F
C,D
4
7-18. The Speedy Pizza Palace is revamping its order-processing and pizza-making procedures. In order to deliver fresh pizza fast, six elements must be completed.
Work Element
Precedence
Time (min)
A Receive order
—
2
B Shape dough
A
1
C Prepare toppings
A
2
D Assemble pizza
B,C
3
E Bake pizza
D
3
F Deliver pizza
E
3
a. Construct a precedence diagram and compute the lead time for the process.
b. If the demand for pizzas is 120 per night (5:00 P.M. to 1:00 A.M.), what is the cycle time?
c. Balance the line and calculate its efficiency.
d. How would the line change to produce 160 pizzas per night?
7-19. Professor Garcia has assigned 15 cases in his OM Seminar class to be completed in a 15-week semester. The students, of course, are moaning and groaning that the caseload cannot possibly be completed in the time allotted. Professor Garcia sympathetically suggests that the students work in groups and learn to organize their work efficiently. Knowing when a situation is hopeless, the students make a list of the tasks that have to be completed in preparing a case. These tasks are listed here, along with precedence requirements and estimated time in days. Assuming students will work five days a week on this assignment, how many students should be assigned to each group, and what is the most efficient allocation of tasks? Can 15 cases be completed in a semester? Explain your answer.
Element
Description
Precedence
Time (days)
a
Read case
—
1
b
Gather data
a
4
c
Search literature
a
3
d
Load in data
b
1
e
Run computer analysis
d
4
f
Write/type case
c,e
4
7-20. The precedence diagram and task times (in minutes) for assembling McCauley's Mystifier are shown here. Set up an assembly line to produce 125 mystifiers in a 40-hour week. Balance the line and calculate its efficiency.
7-21. The precedence diagram and task times (in minutes) for assembling modular furniture are shown below. Set up an assembly line to assemble 1000 sets of modular furniture in a 40-hour week. Balance the line and calculate its efficiency.
7-22. The Costplus Corporation has set a processing quota of 80 insurance claims per 8-hour day. The claims process consists of five elements, which are detailed in the following table. Costplus has decided to use an assembly-line arrangement to process the forms and would like to make sure they have set up the line in the most efficient fashion. Construct a precedence diagram for the claims process and calculate the cycle time required to meet the processing quota. Balance the assembly line and show your arrangement of workstations. Calculate the line's efficiency. How many claims can actually be processed on your line?
Element
Precedence
Performance Time (min)
A
—
4
B
A
5
C
B
2
D
A
1
E
C,D
3
7-23. Given in the following table are the tasks necessary for final assembly of a hospital bed, the length of time needed to perform each task, and the operations that must be completed prior to subsequent operations. Construct a precedence diagram and balance the assembly line for a desired cycle time of 14 minutes. Draw a schematic diagram of the balanced line. How many beds can actually be assembled in an eight-hour period?
Element
Precedence
Time (min)
A
None
4
B
None
5
C
None
8
D
A
4
E
A,B
3
F
B
3
G
D,E
5
H
F
7
I
G,H
1
J
l
7
K
C,J
4
7-24. Given in the following table are the tasks necessary for the assembly of Fine Cedar Chests, the length of time needed to perform each task, and the operations that must be completed prior to subsequent operations.
Element
Precedence
Time (min)
A
None
2
B
A
4
C
B
5
D
None
5
E
D
3
F
None
1
G
F
2
H
C,E,G
4
a. Calculate the cycle time necessary to complete 300 cedar chests in a 35-hour week.
b. What is the minimum number of workstations that can be used on the assembly line and still reach the production quota? Balance the line and calculate the line's efficiency.
c. Rebalance the line with a cycle time of 9 minutes. How do the number of workstations, output, and line efficiency change?
7-25. Quick Start Technologies (QST) helps companies design facility layouts. One of its clients is building five new assembly plants across the continental United States. QST will design the assembly-line layout and ship the layout instructions, along with the appropriate machinery to each new locale. Use the precedence and time requirements given below to design an assembly line that will produce a new product every 12 minutes. Construct a precedence diagram, group the tasks into workstations, determine the efficiency of the line, and calculate the expected output for an eight-hour day.
Task
Precedence
Time (min)
A
None
6
B
A
2
C
B
2
D
A
1
E
A
7
F
A
5
G
C
6
H
D,E,F
5
I
H
3
J
G
5
K
I,J
4
7-26. Print-for-All is a family-owned print shop that has grown from a three-press two-color operation to a full-service facility capable of performing a range of jobs from simple copying to four-color printing, scanning, binding, and more. The company is moving into a new facility and would like some help arranging its 16 processes into an efficient, yet flexible, layout. A list of the most popular jobs is shown with processing information. How would you arrange the processes to ensure an efficient and flexible operation?
Example 7.3 Processes
7-27. Jetaway, a small manufacturer of replacement parts for the aircraft industry, had always maintained a simple layout—all like machines were located together. That way the firm could be as flexible as possible in producing small amounts of the variety of parts its customers required. No one questioned the production arrangement until Chris Munnelly started to work for the company. Chris was actually hired to upgrade Jetaway's computer system. In the process of creating a database of part routings, Chris began to see similarities in the parts produced. A part routing matrix for nine of the most popular parts is shown below, along with a schematic of the factory layout.
Chris, who was already tired of being a programmer, decided to reorder the matrix and see what he could find. If he could identify distinct part families, he could reorganize the placement of machines into the cells he had been reading about in his business magazines. Maybe then someone would notice his management potential.
Help Chris gain status in Jetaway by creating a cellular layout for the company. Show your results in a schematic diagram. Be sure to include the reordered routing matrix.
CASE PROBLEM 7.1 Workout Plus
Workout Plus is a health club that offers a full range of services to its clients. Recently, two other fitness clubs have opened up in town, threatening Workout's solvency. While Workout is tops among serious fitness buffs, it has not attracted a wide spectrum of members. Shannon Hiller, owner and manager, has decided it's time for a face lift. She started the process by sponsoring a week-long “ideathon” among club members. Nonmembers who frequented an adjacent grocery store were also canvassed for suggestions. Their comments are provided below, along with the current facility layout.
Current layout:
Initial Layout
Member comments:
• The cardio machines fill up too fast on rainy days. Then everything else gets backed up.
• I don't feel like strutting through the gym from one end to the other just to finish my workout.
• How about a quick 30-minute workout routine for busy folks?
• I like working out with my friends, but aerobics is not for me. What other group activities are good for cardio?
• Separate the people who want to gab from the people who want to pump.
• It's so confusing with all those machines and weights. You need a novice section that's not so intimidating.
• It's hard to work yourself in when you come from across the gym. I'd like to see the machines I'll be using to gauge my time.
• Circuit training is for wimps. The next thing you know you'll be stopping and starting the music to tell us when to change machines.
• We all seem to arrive at the popular machines at once. Can you space us out?
• I'd like for my kids to get some exercise too while I'm working out. But I don't want them wandering all over the place trying to find me.
• This place is too crowded and disorganized. It's not fun anymore.
• You have classes only at busy times. During the day the gym is empty, but you don't provide many services. I think you're missing a great opportunity to connect with the not-so-fit at off-peak times.
1. How can Workout update its facility to attract new customers? What additional equipment or services would you suggest? How could something as simple as revising the layout help?
2. It is your job to design a new layout for Workout Plus. Visit a nearby gym to get ideas. Watch the customer flow, unused space, and bottlenecks. What aspects of a process layout do you see? a product layout? cells? Draw a simple diagram of your proposed layout. (You'll want to be more detailed than the original layout.) How does your layout respond to the comments collected by Shannon?
CASE PROBLEM 7.2 Photo Op-Please Line Up
Tech is modernizing its college ID system. Beginning this term, all faculty, staff, and students will be required to carry a “smart” identification card, called a student passport. What makes it smart is a magnetic strip with information on club memberships, library usage, class schedules (for taking exams), restrictions (such as no alcohol), medical insurance, emergency contacts, and medical conditions. If desired, it can also be set up as a debit card to pay fines or purchase items from the bookstore, vending machines, cash machines, copy machines, and several local retailers.
University administrators are excited about the revenue potential and increased control of the passport, but they are not looking forward to the process of issuing approximately 60,000 new cards. If applicants could be processed at the rate of 60 an hour, the entire university could be issued passports in a month's time (with a little overtime).
The steps in the process and approximate times follow. Steps 1 and 2 must be completed before step 3 can begin. Steps 3 and 4 must precede step 5, and step 5 must be completed before step 6.
Steps in Process
Time
1. Review application for correctness
10 seconds
2. Verify information and check for outstanding debt
60 seconds
3. Process and record payment
30 seconds
4. Take photo
20 seconds
5. Attach photo and laminate
10 seconds
6. Magnetize and issue passport
10 seconds
a. Is it possible to process one applicant every minute? Explain.
b. How would you assign tasks to workers in order to process 60 applicants an hour?
c. How many workers are required? How efficient is your line?
CASE PROBLEM 7.3 The Grab'n Go Café
The GNG Café, a new concept in on-campus dining features homemade bakery items, upscale sandwiches and wraps, fresh salads, and signature soups. The modern café-style design allows customers the freedom to select their menu choices from individual stations throughout the cafe. While the restaurant has caught the imagination of the university community with its nifty interiors and quality food (which is a welcome change from “the bun”), space and layout restrictions have ensured that the customer when buying anything at GNG can neither “grab” nor “go” with his food.
It is undeniable that the quality of food offered at GNG is good, but GNG management should not forget that their target customers are students who possess a modest income. It is not unusual for students to reach the checkout and find themselves without sufficient funds to complete their transaction.
The first thing customers do when they enter the restaurant is stand and look for the various items they want to buy. While the food and drinks are displayed quite neatly and colorfully, customers still have a hard time figuring out where to go first and what price they should expect to pay for a particular product. Neither the product options nor their prices are prominently displayed. This is especially true of made-to-order sandwiches. Since customers don't have information about the sandwiches beforehand and the options are many, they can take quite some time deciding what kind of sandwich they want to buy. This causes a traffic problem especially at mealtimes when a lot of people come in at the same time to order, and then must wait for their food in a small space. The overcrowding and open layout also present problems with pilfering of food, as students conveniently “forget” to pay upon exiting the facility.
GNG management has agreed to take on a student project to chart the flow of customers through the café and to make recommendations on facility changes. A schematic diagram of the existing layout follows, along with data on the flow of 25 customers. What changes in layout and operating procedures would you recommend for GNG?
Table 7.3 Customer Flow Data
Figure 7.17 GNG Facility Layout
REFERENCES
Benjaafar, Saif, Sunderesh Heragu, and Shahrukh Irani. “Next Generation Factory Layouts: Research Challenges and Recent Progress.” Interfaces (November/December 2002), pp. 58-78.
Black, J. T. The Design of the Factory with a Future. New York: McGraw-Hill, 1991.
Flanders, R. E. “Design, Manufacture and Production Control of a Standard Machine.” Transactions of ASME 46 (1925).
Goetsch, D. Advanced Manufacturing Technology. Albany, NY: Delmar, 1990.
Hyer, Nancy, and Urban Wemmerlov. Reorganizing the Factory: Competing Through Cellular Manufacturing. Portland, OR: Productivity Press, 2002.
Jablonowski, J. “Reexamining FMSs.” American Machinist, Special Report 774 (March 1985).
Luggen, W. Flexible Manufacturing Cells and Systems. Upper Saddle River, NJ: Prentice Hall, 1991.
Monden, Y. Toyota Production System, 3rd ed. Atlanta: IIE Press, 1993.
Muther, R. Systematic Layout Planning. Boston: Industrial Education Institute, 1961.
Russell, R. S., P. Y. Huang, and Y.Y. Leu. “A Study of Labor Allocation in Cellular Manufacturing.” Decision Sciences 22 (3; 1991), pp. 594-611.
Sumichrast, R. T., R. S. Russell, and B. W. Taylor. “A Comparative Analysis of Sequencing Procedures for Mixed-Model Assembly Lines in a Just-In-Time Production System.” International Journal of Production Research 30 (1; 1992), pp. 199-214.
Towards a New Era in Manufacturing Studies Board. Washington, DC: National Academy Press, 1986.
Chapter 7 Supplement to Operational Decision-Making Tools: Facility Location Models
In this supplement, you will learn about…
• Types of Facilities
• Site Selection: Where to Locate
• Global Supply Chain Factors
• Location Analysis Techniques
The physical location of business facilities can have a significant impact on the success of a company. In this supplement we will briefly discuss some of the factors that are important in locating facilities. We will focus on several quantitative methods for facility location, including location factor ratings, the center-of-gravity technique, and the load-distance technique.
TYPES OF FACILITIES
The type of facility is a major determinant of its location. The factors important in determining the location of a manufacturing plant are usually different from those important in locating a service facility or a warehouse. In this section we discuss the major categories of facilities and the different factors that are important in the location desired.
Heavy manufacturing facilities are plants that are large, require a lot of space, and are expensive to construct, such as automobile plants, steel mills, and oil refineries.
Factors in the location decision for plants include construction costs, land costs, modes of transportation for shipping heavy manufactured items and receiving bulk shipments of raw materials, proximity to raw materials, utilities, means of waste disposal, and labor availability. Sites for manufacturing plants are normally selected where construction and land costs can be kept at a minimum and raw material sources are nearby in order to reduce transportation costs. Access to railroads is frequently a factor in locating a plant. Environmental issues have increasingly become a factor in plant location decisions.
Henry-manufacturing facilities are large, require a lot of space, and are expensive.
light-industry facilities are smaller, cleaner plants and are usually less costly.
Retail and service facilities are the smallest and least costly.
Light-industry facilities are perceived as cleaner plants that produce electronic equipment and components, computer products, or assembled products like TVs; breweries; or pharmaceutical firms.
Distribution centers for The Gap in Gallatin. Tennessee, Target in Augusta City, Virginia, and Home Depot in Savannah. Georgia, each encompass more than 1.4 million square feet of space—about 30 times bigger than the area of a football field! The UPS Worldwide Logistics warehouse in Louisville, Kentucky, includes 1.3 million square feet of floor space. Because of their role as intermediate points in the supply chain, transportation costs are often an important factor in the location decision for warehouses. The proximity to markets is also a consideration, depending on the delivery requirements, including frequency of delivery required by the customer.
Retail and service facilities are usually the smallest and least costly. Examples include retail facilities such as groceries and department stores, among many others, and such service facilities as restaurants, banks, hotels, cleaners, clinics, and law offices. However, there are always exceptions, and some service facilities, such as a hospital, a company headquarters, a resort hotel, or a university academic building can be large and expensive. One of the most important factors for locating a service or retail facility is proximity to customers. It is often critical that a service facility be near the customers it serves, and a retail facility must be near the customers who buy from it. Construction costs tend to be less important, although land or leasing costs can be high. For retail operations, for which the saying “location is everything” is meaningful, site costs can be very high. Factors like zoning, utilities, transportation, environmental constraints, and labor tend to be less important for service operations, and closeness to suppliers is not usually as important as it is to manufacturing firms, which must be close to materials and parts suppliers.
SITE SELECTION: WHERE TO LOCATE
When we see in the news that a company has selected a site for a new plant, or a new store is opening, the announcement can appear trivial. Usually it is reported that a particular site was selected from among two or three alternatives, and a few reasons are provided, such as good community, heavy customer traffic, or available land. However, such media reports do not reveal the long, detailed process for selecting a site for a business facility. It is usually the culmination of a selection process that can take several years and the evaluation of dozens or hundreds of potential sites.
Decisions regarding where to locate a business facility or plant are not made frequently, but they tend to be crucial in terms of a firm's profitability and long-term survival. A mistake in location is not easily overcome. Business success often is being “in the right place at the right time.” For a service operation such as a restaurant, hotel, or retail store, being in the right place usually means in a location that is convenient and easily accessible to customers.
Location decisions for services tend to be an important part of the overall market strategy for the delivery of their products or services to customers. However, a business cannot simply survey the demographic characteristics of a geographic area and build a facility at the location with the greatest potential for customer traffic; other factors, particularly financial considerations, must be part of the location decision. Obviously, a site on Fifth Avenue in New York City would be attractive for a McDonald's restaurant, but can enough hamburgers and french fries be sold to pay the rent? In this case, the answer is yes.
Location decisions are usually made more frequently for service operations than manufacturing facilities. Facilities for service-related businesses tend to be smaller and less costly, although a hospital, or hotel can require a huge investment and be very large. Services depend on a certain degree of market saturation; the location is actually part of their product. Where to locate a manufacturing facility is also important, but for different reasons, not the least of which is the very high expense of building a plant or factory. Although the primary location criteria for a service-related business is usually access to customers, a different set of criteria is important for a manufacturing facility. These include the nature of the labor force, and labor costs, proximity to suppliers and markets, distribution and transportation costs, energy availability and cost, the community infrastructure of roads, sewers, and utilities, quality of life in a community, and government regulations and taxes.
When the site selection process is initiated, the pool of potential locations for a manufacturing or service facility is, literally, global. In today's international marketplace, countries around the world become potential sites. The site selection process is one of gradually and methodically narrowing down the pool of alternatives until the final location is determined. In the following discussion, we identify some of the factors that companies consider when determining the country, region, community, and site at which to locate a facility.
GLOBAL SUPPLY CHAIN FACTORS
In recent years U.S. companies have begun to locate in foreign countries to be closer to newly emerging markets and to take advantage of lower labor costs. Trade agreements between countries have reduced trade barriers around the world and created new markets like the European Community (EC), Eastern Europe, and Asia.
Foreign firms have also begun to locate in the United States to be closer to their customers. For both U.S. and foreign companies, the motivation is the same—to reduce supply chain costs and better serve their customers. Relatively slow overseas transportation requires multinational companies to maintain large, costly inventories to serve their foreign customers in a timely manner. This drives up supply chain costs and makes it economical for companies to relocate closer to their markets.
While foreign markets offer great opportunities, the problems with locating in a foreign country can be substantial, making site location a very important part of supply chain design. For example, although China offers an extremely attractive market because of its huge population, growing economy, and cheap labor force, it has an inefficient transportation and distribution system, and numerous government regulations. Markets in Russia and the former Soviet states are attractive; however they can also be risky since the free market economy is still new to these states. Lack of familiarity with standard business practices and corruption can threaten success for foreign companies.
Some of the factors that multinational firms must consider when locating in a foreign country include the following:
• Government stability
• Government regulations
• Political and economic systems
• Economic stability and growth
• Exchange rates
• Culture
• Climate
• Export and import regulations, duties, and tariffs
• Raw material availability
• Number and proximity of suppliers
• Transportation and distribution systems
• Labor force cost and education
• Available technology
• Commercial travel
• Technical expertise
• Cross-border trade regulations
• Group trade agreements
REGIONAL AND COMMUNITY LOCATION FACTORS IN THE UNITED STATES
Manufacturing facilities in the United States were historically located in the Midwest, especially in the Great Lakes region. Industry migrated to the sunbelt areas, the Southeast and Southwest, during the 1960s and 1970s, where labor was cheaper (and not unionized), the climate was better, and the economy was growing. However, in the late 1990s, there was a perceptible shift in new plants and plant expansion back to the nation's agricultural heartland. The North Central region, consisting of Illinois, Michigan, and Ohio, attracted new and expanded facilities as did the South Atlantic region.
Certain states are successful in attracting new manufacturing facilities for a variety of reasons. Ohio, for example, is well located along the Interstate-75 corridor, and it is within one-day truck delivery of 60% of the U.S. population and two-thirds of its purchasing power. It has a good base of skilled and educated labor, a large mass of industry that spawns other businesses, and it has established good incentive programs to attract new businesses. Ohio also benefits from a number of towns and cities with populations less than 50,000 that have a rich agricultural heritage. The residents of these communities have a strong work ethic and are self-reliant and neighborly. These communities typically have quality health services; low crime rates; solid infrastructures of roads, water and sewer systems; open spaces to expand; and quality education.
The most growth in manufacturing facilities is in the Midwest.
Ohio attracts manufacturing facilities: because of good transportation, skilled labor with a strong work ethic, incentive programs, and quality social services.
Labor—cost, availability, work ethic, conflict, and skill—is important in a company's location decision.
Closeness to customers can be a factor in providing quality service.
Service facilities generally require high customer-traffic volume.
Infrastructure:
the roads, water and sewer, and utilities at a location.
Labor is one of the most important factors in a location decision, including the cost of labor, availability, work ethic, the presence of organized labor and labor conflict, and skill and educational level. Traditionally, labor costs have been lower and organized labor has been less visible across the South and Southwest. While labor conflict is anathema to many companies, in some cases labor unions have assisted in attracting new plants or in keeping existing plants from relocating by making attractive concessions.
The proximity of suppliers and markets are important location factors. Manufacturing companies need to be close to materials, and service companies like fast-food restaurants, retail stores, groceries, and service stations need to be close to customers and distribution centers. Transportation costs can be significant if frequent deliveries over long distances are required. The closeness of suppliers can determine the amount of inventory a company must keep on hand and how quickly it can serve its own customers. Uncertainty in delivery schedules from suppliers can require excessive inventories.
It is important for service-related businesses to be located near their customers. Many businesses simply look for a high volume of customer traffic as the main determinant of location, regardless of the competition. An interstate highway exit onto a major thoroughfare always has a number of competing service stations and fast-food restaurants. Shopping malls are an example of a location in which a critical mass of customer traffic is sought to support a variety of similar and dissimilar businesses.
Another important factor, infrastructure , is the collection of physical support systems of a location, including the roads, water and sewer, and utilities. If a community does not have a good infrastructure, it must make improvements if it hopes to attract new business facilities. From a company's perspective, an inadequate infrastructure will add to its supply chain costs and inhibit its customer service.
Factors that are considered when selecting the part of the country and community for a facility are summarized as follows:
• Labor (availability, education, cost, and unions)
• Proximity of customers
• Number of customers
• Construction/leasing costs
• Land cost
• Modes and quality of transportation
• Transportation costs
• Community government
• Local business regulations
• Government services (e.g., Chamber of Commerce)
• Financial services
• Community inducements
• Business climate
• Community services
• Incentive packages
• Government regulations
• Environmental regulations
• Raw material availability
• Commercial travel
• Climate
• Infrastructure (e.g., roads, water, sewers)
• Quality of life
• Taxes
• Availability of sites
• Proximity of suppliers
• Education system
Location incentives include tax credits, relaxed government regulations, job training, infrastructure improvements, and money.
LOCATION INCENTIVES
Besides physical and societal characteristics, local incentives have increasingly become a major important factor in attracting companies to specific locations. Incentive packages typically include job tax credits, relaxed government regulations, job training, road and sewage infrastructure improvements, and sometimes just plain cash. These incentives plus the advantages of a superior location can significantly reduce a company's supply chain costs while helping it achieve its strategic goal for customer service.
States and communities cannot afford to overlook incentives if they hope to attract new companies and jobs. However, they must make sure that the amount of their investment in incentive packages and the costs they incur for infrastructure improvements are balanced against the number of new jobs developed and the expansion of the economy the new plant will provide. Incentives are a good public investment unless they bankrupt the locality. While some small communities are successful in attracting new businesses, they are left with little remaining tax base to pay for the infrastructure improvements needed to support the increased population drawn by job demand. Thus, states and communities, much like businesses, need a strategy for economic development that weighs the costs versus the benefits of attracting companies.
GEOGRAPHIC INFORMATION SYSTEM
A recent information technological advancement that is increasingly being used in the facility location and site selection process is a geographic information system or GIS. A GIS is a computerized system for storing, managing, creating, analyzing, integrating, and digitally displaying geographic (i.e spatial, data). A GIS is both a database system as well as a set of operations for working with and analyzing this data. As a tool specifically used for site selection, it allows the user to interactively search and analyze the type of data and information (i.e., location factors) we discussed in the previous sections that might be related to the site selection process, such as population, labor, income, customer base, climate, taxes, and transportation. Frequently a GIS used for site selection will incorporate quantitative models (like the ones presented later in this chapter and text) to help analyze the data.
Figure S7.1 provides a simple schematic diagram of how a GIS for site selection might be constructed. Each layer (or spatial map) in this diagram contains information about one characteristic (or attribute) of the location begin analyzed. Each layer that might relate to the site selection process is precisely overlaid on the other layers so that their corresponding geographic (spatial, locations) are exactly matched to each other. The bottom layer is a geographic grid that serves as a frame of reference (e.g., latitude and longitude), to which all the other layers are precisely matched.
Once these layers of data have been entered into the GIS, information about the layers can be compared and analyzed in combination. For example, transportation routes can be considered relative to the location of plants, distribution centers, and shippers, as well as labor markets and natural resources, such as water. Such comparative analyses are frequently in the form of digital computer displays as well as three-dimensional graphs and displays. The GIS may provide just statistical analyses for use in the decision-making process, or it may incorporate one or more quantitative models to provide a recommended decision about a site.
The advantage of a GIS is that it enables the user to integrate large quantities of information about potential facility sites and then analyze these data with a number of different, powerful analytical tools. The ability to consider hundreds of separate layers of spatial information and then combine it with other layers of information is the main reason GIS has become such a popular tool for location analysis and site selection.
One of the first major uses of GIS was in environmental and natural resources planning, and land use management for the analysis of such things as agricultural lands, wildlife habitat, wetlands, floodplains, and forests. It has also come to be used extensively for utilities and infrastructure planning and management, including such things as energy use, cable and pipe networks, gas lines, electrical usage and networks, and transportation, as well as real estate analysis, demographic and marketing analysis, and various government applications such as emergency services and analyzing tax bases. However, in recent years GIS has come to be used more and more in business applications. For example, GIS has been used to select distribution centers or hubs based on spatial data for shipping times, customer locations, transportation routes, etc. Bank of America upon entering the New York City market used a GIS to show the distribution of its own branch network relative to deposit potential in the New York market area; from this they determined where their market coverage was strong or weak. Levi Strauss used a GIS to create a geographic network of its existing retailers, potential retailers, and the customer base each served, so it could make sure that new stores that joined its retail network would not adversely affect sales in existing stores. Edens & Avant, one of the nation's leading retail real estate companies, has a GIS-based Web site that enables retailers to locate space in their inventory (at various shopping malls, etc.) that specifically matches their site selection criteria.
Today there are hundreds of commercial software systems that offer GIS capabilities for different applications including site selection, and numerous consulting and software firms that specialize in the development of GIS for specific applications. The list of Web sites for this supplement includes links to several GIS software systems and some of the major companies that specialize in GIS development and applications.
Figure S7.1 A GIS Diagram
• Internet Exercises
LOCATION ANALYSIS TECHNIQUES
We will discuss three techniques to help make a location decision—the location rating factor, the center-of-gravity technique, and the load-distance technique. The location factor rating mathematically evaluates location factors, such as those identified in the previous section. The center-of-gravity and load-distance techniques are quantitative models that centrally locate a proposed facility among existing facilities.
LOCATION FACTOR RATING
The decision where to locate is based on many different types of information and inputs. There is no single model or technique that will select the “best” site from a group. However, techniques are available that help to organize site information and that can be used as a starting point for comparing different locations.
In the location factor rating system, factors that are important in the location decision are identified. Each factor is weighted from 0 to 1.00 to prioritize the factor and reflect its importance. A subjective score is assigned (usually between 0 and 100) to each factor based on its attractiveness compared with other locations, and the weighted scores are summed. Decisions typically will not be made based solely on these ratings, but they provide a good way to organize and rank factors.
Location factor rating:
a method for identifying and weighting important location factors.
Example S7.1 Location Factor Rating
The Dynaco Manufacturing Company is going to build a new plant to manufacture ring bearings (used in automobiles and trucks). The site selection team is evaluating three sites, and they have scored the important factors for each as follows. They want to use these ratings to compare the locations.
Solution
The weighted scores for each site are computed by multiplying the factor weights by the score for that factor. For example, the weighted score for “labor pool and climate” for site 1 is
(0.30)(80) = 24 points
The weighted scores for each factor for each site and the total scores are summarized as follows:
Site 3 has the highest factor rating compared with the other locations; however, this evaluation would have to be used with other information, particularly a cost analysis, before making a decision.
LOCATION FACTOR RATING WITH EXCEL AND OM TOOLS
Exhibit S7.1 shows the Excel spreadsheet for Example S7.1. Notice that the location score for Site 1 is shown in cell E12 and the formula for the computation of the site 1 score (embedded in E12) is shown on the formula bar at the top of the spreadsheet.
Exhibit S7.2 shows the OM Tools spreadsheet for Example S7.1
• Excel File
Exhibit S7.1
Exhibit S7.2
• OM Tools
Center-of-gravity technique:
the center of movement in a geographic area based on transport weight and distance.
CENTER-OF-GRAVITY TECHNIQUE
In general, transportation costs are a function of distance, weight, and time. The center-of-gravity, or weight center, technique is a quantitative method for locating a facility such as a warehouse at the center of movement in a geographic area based on weight and distance. This method identifies a set of coordinates designating a central location on a map relative to all other locations.
The starting point for this method is a grid map set up on a Cartesian plane, as shown in Figure S7.2. There are three locations, 1, 2, and 3, each at a set of coordinates (xi, yi) identifying its location in the grid. The value Wi is the annual weight shipped from that location. The objective is to determine a central location for a new facility.
Figure S7.2 Grid Map Coordinates
The coordinates for the location of the new facility are computed using the following formulas:
where
x, y = coordinates of the new facility at center of gravity
xi, yi = coordinates of existing facility i
Wi = annual weight shipped from facility i
Example S7.2 The Center-of-Gravity Technique
The Burger Doodle restaurant chain purchases ingredients from four different food suppliers. The company wants to construct a new central distribution center to process and package the ingredients before shipping them to their various restaurants. The suppliers transport ingredient items in 40-foot truck trailers, each with a capacity of 38,000 lbs. The locations of the four suppliers, A, B, C, and D, and the annual number of trailer loads that will be transported to the distribution center are shown in the following figure:
Using the center-of-gravity method, determine a possible location for the distribution center.
Solution
A
B
C
D
xA = 200
xB = 100
xC = 250
xD = 500
yA = 200
yB = 500
yC = 600
yD = 300
WA = 75
WB = 105
WC = 135
WD = 60
Thus, the suggested coordinates for the new distribution center location are x = 238 and y = 444. However, it should be kept in mind that these coordinates are based on straight-line distances, and in a real situation actual roads might follow more circuitous routes.
CENTER-OF-GRAVITY TECHNIQUE WITH EXCEL AND OM TOOLS
Exhibit S7.3 shows the Excel spreadsheet for Example S7.2. The formula for computing the x-coordinate in cell C13 is shown on the formula bar at the top of the spreadsheet.
Exhibit S7.4 on the next page shows the OM Tools spreadsheet for Example S7.2.
LOAD-DISTANCE TECHNIQUE
A variation of the center-of-gravity method for determining the coordinates of a facility location is the load-distance technique . In this method, a single set of location coordinates is not identified.
• Excel File
Load-distance technique:
a method of evaluating different locations based on the load being transported and the distance.
Exhibit S7.3
Exhibit S7.4
• OM Tools
Instead, various locations are evaluated using a load-distance value that is a measure of weight and distance. For a single potential location, a load-distance value is computed as follows:
where
LD = the load-distance value
li = the load expressed as a weight, number of trips, or units being shipped from the proposed site to location i
di = the distance between the proposed site and location i
The distance di in this formula can be the travel distance, if that value is known, or can be determined from a map. It can also be computed using the following formula for the straight-line distance between two points, which is also the hypotenuse of a right triangle:
where
(x, y) = coordinates of proposed site
(xi, yi) = coordinates of existing facility
The load-distance technique is applied by computing a load-distance value for each potential facility location. The implication is that the location with the lowest value would result in the minimum transportation cost and thus would be preferable.
Example S7.3 The Load-Distance Technique
Burger Doodle wants to evaluate three different sites it has identified for its new distribution center relative to the four suppliers identified in Example S7.2. The coordinates of the three sites under consideration are as follows:
Site 1: x1 = 360, y1 = 180
Site 2: x2 = 420, y2 = 450
Site 3: x3 = 250, y3 = 400
Solution
First, the distances between the proposed sites (1, 2, and 3) and each existing facility (A, B, C, and D), are computed using the straight-line formula for di:
Next, the formula for load distance is computed for each proposed site:
Since site 3 has the lowest load-distance value, it would be assumed that this location would also minimize transportation costs. Notice that site 3 is very close to the location determined using the center-of-gravity method in Example S7.2.
LOAD-DISTANCE TECHNIQUE WITH EXCEL AND OM TOOLS
Exhibit S7.5 shows the Excel spreadsheet for Example S7.3. The formula for computing the distance from supplier location A to site 1 is embedded in C11 and is shown on the formula bar at the top of the spreadsheet. The formula for computing the location-distance formula for site 1 is shown in the call out box attached to cell C17.
Exhibit S7.6 shows the OM Tools spreadsheet for Example S7.3.
• Excel File
Exhibit S7.5
Exhibit S7.6
• OM Tools
• Practice Quizzes
SUMMARY
Facility location is an often overlooked but important aspect of a company's strategic plan. What kind of facility to build and where to locate it are expensive decisions. A location decision is not easily reversed if it is a bad one. For a service operation, the wrong location can result in too few customers to be profitable, whereas for a manufacturing operation, a wrong location can result in excessive costs, especially for transportation and distribution, and high inventories. The quantitative tools presented in this supplement are not usually sufficient for making an actual location decision, but they do provide means for helping in the location analysis and decision process.
SUMMARY OF KEY FORMULAS
Center-of-Gravity Coordinates
Load-Distance Technique
SUMMARY OF KEY TERMS
center-of-gravity technique
a quantitative method for locating a facility at the center of movement in a geographic area based on weight and distance.
infrastructure
the physical support structures in a community, including roads, water and sewage systems, and utilities.
load-distance technique
a quantitative method for evaluating various facility locations using a value that is a measure of weight and distance.
location factor rating
a system for weighting the importance of different factors in the location decision, scoring the individual factors, and then developing an overall location score that enables a comparison of different location sites.
SOLVED PROBLEMS
Animated Demo Problem
1. CENTER-OF-GRAVITY TECHNIQUE
A company is going to construct a new warehouse served by suppliers A, B, and C. The locations of the three suppliers and the annual number of truck carriers that will serve the warehouse are shown in the following figure:
Determine the best site for the warehouse using the center of gravity technique.
SOLUTION
The suggested coordinates for the new warehouse are x = 290.5 and y = 311.9.
QUESTIONS
S7-1. How are the location decisions for service operations and manufacturing operations similar, and how are they different?
S7-2. Indicate what you perceive to be general location trends for service operations and manufacturing operations.
S7-3. What factors make the southern region of the United States an attractive location for service and manufacturing businesses?
S7-4. Describe the positive and negative factors for a company contemplating locating in a foreign country.
S7-5. What would be the important location factors that McDonald's might consider before opening a new restaurant?
S7-6. The following businesses are considering locating in your community:
a. A pizza delivery service
b. A sporting goods store
c. A small brewery
d. A plant making aluminum cans
Describe the positive and negative location factors for each of these businesses.
S7-7. What location factors make small cities and towns in the Midwest attractive to companies?
S7-8. Select a major (light or heavy) manufacturing facility in your community or immediate geographic area (within a radius of 100 miles), and identify the factors that make it a good or poor site, in your opinion.
S7-9. Assume that you are going to open a Starbuck's is in your community. Select three sites. Perform a location factor analysis for each and select the best site.
S7-10. Suppose your college or university was planning to develop a new student center and athletic complex with a bookstore, theaters, meeting areas, pool, gymnasium, and weight and exercise rooms. Identify three potential sites on your campus for this facility and rank them according to location factors you can identify.
S7-11. Select four fast-food restaurants (e.g., McDonald's, Burger King, Wendy's, Domino's, etc.) in your town, and develop a scoring model including decision criteria, weights, and grades to rank the restaurants from the best to worst.
PROBLEMS
• GO Tutorial
S7-1. Sweats and Sweaters is a small chain of stores specializing in casual cotton clothing. The company currently has five stores in Georgia, South Carolina, and North Carolina, and it wants to open a new store in one of four new mall locations in the Southeast. A consulting firm has been hired to help the company decide where to locate its new store. The company has indicated five factors that are important to its decision, including proximity of a college, community median income, mall vehicle traffic flow and parking, quality and number of stores in the mall, and proximity of other malls or shopping areas. The consulting firm had the company weight the importance of each factor. The consultants visited each potential location and rated them according to each factor, as follows:
Given that all sites have basically the same leasing costs and labor and operating costs, recommend a location based on the rating factors.
S7-2. Exotech Computers manufactures computer components such as chips, circuit boards, motherboards, keyboards, LCD panels, and the like and sells them around the world. It wants to construct a new warehouse/distribution center in Asia to serve emerging Asian markets. It has identified sites in Shanghai, Hong Kong, and Singapore and has rated the important location factors for each site as follows:
Recommend a site based on these location factors and ratings.
S7-3. State University is going to construct a new student center and athletic complex that will include a bookstore, post office, theaters, market, mini-mall, meeting rooms, swimming pool, and weight and exercise rooms. The university administration has hired a site selection specialist to identify the best potential sites on campus for the new facility. The site specialist has identified four sites on campus and has rated the important location factors for each site as follows:
Recommend a site based on these location factors and ratings.
S7-4. Arsenal Electronics is going to construct a new $1.2 billion semiconductor plant and has selected four towns in the Midwest as potential sites. The important location factors and ratings for each town are as follows:
Recommend a site based on these location factors and ratings.
S7-5. Herriott Hotels. Inc. wants to develop a new beachfront resort along the coast of South Carolina. A number of sites are available, and the hotel chain has narrowed the choice to five locations. They have graded their choices according to the weighted criteria shown as follows:
Recommend a resort site based on these location factors and ratings.
S7-6. Robin Dillon has recently accepted a new job in the Washington, DC, area and has been hunting for a condominium to purchase. From friends and coworkers she has compiled a list of five possible condominium complexes that she might move into. The following table indicates the weighted criteria that Robin intends to use in her decisionmaking process and a grade indicating how well each complex satisfies each criterion.
S7-7. Balston Healthcare operates three hospitals and a number of clinics in its citywide network. It is planning to open a new wellness center and clinic facility that focuses on geriatric clients in one of four suburbs. The following table shows the weighted criteria for each location.
Recommend a site for the new Balston Healthcare facility based on these weighted location factors and scores.
S7-8. The owners of the Midlands United professional soccer team currently located in a Midwestern city are concerned about declining attendance at their team's games, and they have decided to use a scoring model to help them decide which city in the south to relocate in—Atlanta, Binning-ham, Charlotte, or Durham. They have graded the possible cities according to the following weighted criteria:
Develop a scoring model to help the owners decide on which city to select to relocate.
S7-9. As part of an aggressive expansion plan, StarTrack Coffee is planning to open three new retail stores in the city. The table on the previous page shows the location factors it considers important indicators of future profitability, and how each location has been graded by management according to each one of these factors.
Use your own judgment to determine weights for each of the location factors and recommend the three new store sites. Are there other location factors that you think might be important?
S7-10. Federated Electronics, Ltd., manufactures display screens and monitors for computers and televisions, which it sells to companies around the world. It wants to construct a new warehouse and distribution center in Asia to serve emerging markets there. It has identified potential sites in the port cities of Shanghai, Singapore, Pusan, Kaohsiung, and Hong Kong. The following table shows the factors in the location decision and the grade of each location for each factor.
The weights indicating the importance of each location factor are not included. Determine what you think these weights should be and recommend the best location for the new distribution center.
S7-11. The Federal Parcel Service wants to build a new distribution center in Charlotte, North Carolina. The center needs to be in the vicinity of uncongested Interstate-77 and Interstate-85 interchanges, and the Charlotte-Douglas International Airport. The coordinates of these three sites and the number of weekly packages that flow to each are as follows:
1-77
1-85
Airport
x = 14
x = 20
x = 30
y = 30
y = 8
y = 14
w = 17.000
w = 12,000
w = 9000
Determine the best site location using the center-of-gravity technique.
S7-12. The Burger Doodle restaurant chain uses a distribution center to prepare the food ingredients it provides its individual restaurants. The company is attempting to determine the location for a new distribution center that will service five restaurants. The grid-map coordinates of the five
Restaurants and the annual number of 40-foot trailer trucks transported to each restaurant are as follows:
Coordinates
Restaurant
x
y
Annual truck shipments
1
100
300
35
2
210
180
24
3
250
400
15
4
300
150
19
5
400
200
38
a. Determine the least-cost location using the center-of-gravity method.
b. Plot the five restaurants and the proposed new distribution center on a grid map.
S7-13. The Burger Doodle restaurant chain in Problem S7-12 is considering three potential sites, with the following grid-map coordinates, for its new distribution center: A(350, 300), B(150, 250), and C(250, 300). Determine the best location using the load-distance formula, and plot this location on a grid map with the five restaurants. How does this location compare with the location determined in Problem S7-12?
S7-14. A development company is attempting to determine the location for a new outlet mall. The region where the outlet mall will be constructed includes four towns, which together have a sizable population base. The grid-map coordinates of the four towns and the population of each are as follows:
Coordinates
Town
x
y
Population (10,000s)
Four Corners
30
60
8.5
Whitesburg
50
40
6.1
Russellville
10
70
7.3
Whistle Stop
40
30
5.9
a. Determine the best location for the outlet mall using the center-of-gravity method.
b. Plot the four towns and the location of the new mall on a grid map.
S7-15. State University in Problem S7-3 is attempting to locate the best site for a new student center and athletic complex. The university administration would like to know what the best location is relative to the four main concentrations of student housing and classroom activity on campus. These coordinates of these housing and classroom areas (in yards) and daily student populations are shown on the previous page. Determine the best site using the center-of-gravity method.
S7-16. Mega-Mart, a discount store chain, wants to build a new superstore in an area in southwest Virginia near four small towns with populations between 8000 and 42,000. The coordinates (in miles) of these four towns and the market population in each are as follows:
Whitesburg
Altonville
Camburg
Milligan
x = 1l
x = 18
x = 30
x = 32
y = 20
y = 15
y = 7
y = 25
w = 26,000
w = 12,000
w = 18,300
w = 9700
Determine the best site using the center-of-gravity technique.
S7-17. Home-Base, a home improvement/building supply chain, is going to build a new warehouse facility to serve its stores in six North Carolina cities—Charlotte, Winston-Salem, Greensboro, Durham, Raleigh, and Wilmington. The coordinates of these cities (in miles), using Columbia, South Carolina, as the origin (0,0) of a set of coordinates, and the annual truckloads that supply each city are shown as follows:
Charlotte
Winston-Salem
Greensboro
x = 15
x = 42
x = 88
y = 85
y = 145
y = 145
w = 160
w = 90
w = 105
Durham
Raleigh
Wilmington
x = 125
x = 135
x = 180
y = 140
y = 125
y = 18
w = 35
w = 60
w = 75
a. Determine the best site using the center-of-gravity technique.
b. Look at a map of North Carolina, and identify the closest town to the grid coordinates developed in Part (a). Looking at the map, can you suggest a better location in the vicinity? Explain your answer.
S7-18. In Problem S7-17. Home-Base has two parcels of land in Fayetteville and Statesville. North Carolina. Use the load-distance technique (and a map of North Carolina) to determine which would be better.
S7-19. An army division in Iraq has five troop encampments in the desert, and the division leaders want to determine the best location for a supply depot to serve the camps. The (x, y) coordinates (in miles) of the camps. A, B. C, D, and E, and the daily amount of supplies (in tons) required at each camp are as follows:
Coordinates
Camp
x
y
Daily tonnage (1000s)
A
110
120
85
B
70
300
110
C
520
350
75
D
300
450
60
E
400
600
100
Determine the best site for the supply depot using the center-of-gravity technique.
S7-20. In Problem S7-19, suppose the division commanders are limited to three possible sites for the supply depot because of airfield locations and enemy troop concentrations. The coordinates (in miles) of these three potential sites are site 1 (400, 250), site 2 (100, 200), and site 3 (200, 500). Using the load-distance technique, determine the best site for the supply depot.
S7-21. Somerset Furniture Company imports furniture components and pieces from several manufactures in China and then assembles the finished furniture pieces and adds hardware at a distribution center before shipping the finished pieces of furniture on to its customers' warehouses in several states. Furniture shipments arrive from China (in containers) at three U.S. ports in the United States—New Orleans, Savannah, and Norfolk. These containers are then transported to Somerset's distribution center for final furniture assembly before they are shipped in truckloads to five customer warehouses. The (x, y) coordinates of the ports and warehouses and the annual container truckload shipments are shown in the following table.
Coordinates
Port/Warehouse
x
y
Annual Truckloads
New Orleans
1100
700
41
Savannah
2700
1400
27
Norfolk
2800
2200
34
1
200
1200
18
2
1400
1500
20
3
700
2300
32
4
1200
2700
24
5
2100
2600
18
Determine the best site for Somerset's distribution center using the center-of-gravity technique. $7-22. In Problem S7-21 suppose Somerset furniture is considering three possible sites for its distribution center, which are the most economical in terms of land and building cost. The coordinates for the three potential sites are site A (1700, 800), site B (2400, 1700), and site C (1800, 2200). Using the load-distance technique, determine the best site for the distribution center.
CASE PROBLEM S7.1 Selecting a European Distribution Center Site for American International Automotive Industries
American International Automotive Industries (AlAl) manufactures auto and truck engine, transmission, and chassis parts for manufacturers and repair companies in the United States, South America, Canada, Mexico, Asia and Europe. The company transports to its foreign markets by container ships. To serve its customers in South America and Asia, AIAI has large warehouse/distribution centers. In Europe it ships into Hamburg and Gdansk, where it has contracted with independent distribution companies to deliver its products to customers throughout Europe. However, AIAI has been displeased with a recent history of late deliveries and rough handling of its products. For a time AIAI was not overly concerned since its European market wasn't too big and its European customers didn't complain. In addition, it had more pressing supply chain problems elsewhere. In the past five years, since trade barriers have fallen in Europe and Eastern European markets have opened up, its Europeans business has expanded, as has new competition, and its customers have become more demanding and quality conscious. As a result, AIAI has initiated the process to select a site for a new European warehouse/distribution center. Although it provides parts to a number of smaller truck, and auto maintenance and service centers in Europe, it has seven major customers—auto and truck manufacturers in Vienna, Leipzig, Budapest, Prague, Krakow, Munich, and Frankfurt. Its customers in Vienna and Budapest have adopted manufacturing processes requiring continuous replenishment of parts and materials.
AIAI's European headquarters is in Hamburg. The vice-president for construction and development in Dayton, Ohio, has asked the Hamburg office to do a preliminary site search based on location, geography, transportation, proximity to customers, and costs. The Hamburg office has identified five potential sites in Dresden, Lodz, Hamburg, Gdansk, and Frankfurt. The Hamburg office has forwarded information about each of these sites to corporate headquarters, including forecasts of the number of containers shipped annually to each customer as follows: Vienna, 160; Leipzig, 100; Budapest. 180; Prague, 210; Krakow, 90; Munich, 120; and Frankfurt, 50. When the vice-president of construction in Dayton received this information, he pulled out his map of Europe and began to study the sites.
Assist AIAI with its site selection process in Europe. Recommend a site form the five possibilities, and indicate what other location factors you might consider in the selection process.
Chapter 13 Inventory Management
Web resources for this chapter include
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▸ Company and Resource Weblinks
www.wiley.com/college/russell
In this chapter, you will learn about …
• The Role of Inventory in Supply Chain Management
• Inventory and Quality Management in the Supply Chain
• The Elements of Inventory Management
• Inventory Control Systems
• Economic Order Quantity Models
• Quantity Discounts
• Reorder Point
• Order Quantity for a Periodic Inventory System
Inventory Management AT MARS
Mars purchases a huge number of raw materials it uses to produce its chocolate (and other) products. Ordering these materials inefficiently wherein they hold too much raw material in inventory results in excessive inventory costs, thus Mars seeks to manage its inventory along its supply chain such that these costs are minimized. Mars relies on a small number of suppliers for each of the large number of materials it purchases to produce its products, and it procures these materials in a number of ways. One increasingly popular means for material procurement at Mars is through electronic auctions, in which Mars buyers negotiate bids for orders with suppliers online. The most important “strategic” purchases are of high value and large volume in which suppliers provide quantity discounts that they specify as a supply curve with an order quantity range associated with each price level (see a similar figure in this chapter in Figure 13.5).
Quantity-discount auctions with supply curves are tailored to industries in which volume discounts are common, such as bulk agricultural commodities like Mars uses. The supplier provides its bid as a supply curve (i.e., a quantity-discount schedule), and the auction may be for one product or many. A Mars buyer selects the bids that minimize total procurement costs subject to several rules—there must be a minimum and maximum number of suppliers so that Mars is not dependent on too few suppliers nor loses quality control over too many; there must be a maximum amount purchased from each supplier to limit the influence of any one supplier; and a minimum amount must be ordered that avoids economically inefficient orders (for example, less than a full truckload).
In this chapter we will learn about the different inventory models and techniques that companies like Mars uses to determine the lowest cost amount of inventory to order and keep on hand, which is one of the primary goals of supply chain management.
Source: G. Hohner, J. Rich, E. Ng, A. Davenport, J. Kalagnanam, H. Lee, and C. An, “Combinatorial and Quantity-Discount Procurement Auctions Benefit Mars, Incorporated and its Suppliers,” Interfaces 33 (1; January-February 2003), pp. 23–35.
The objective of inventory management has been to keep enough inventory to meet customer demand and also be cost effective. However, inventory has not always been perceived as an area to control cost. Traditionally, companies maintained “generous” inventory levels to meet long-term customer demand because there were fewer competitors and products in a generally sheltered market environment. In the current global business environment, with more competitors and highly diverse markets in which new products and new product features are rapidly and continually introduced, the cost of inventory has increased due in part to quicker product obsolescence. At the same time, companies are continuously seeking to lower costs so they can provide a better product at a “lower” price.
Inventory is an obvious candidate for cost reduction. The U.S. Department of Commerce estimates that U.S. companies carry $1.1 trillion in inventory spread out along the supply chain with $450 billion at manufacturers, $290 billion at wholesalers and distributors, and $400 billion at retailers. It is estimated that the average holding cost of manufacturing goods inventory in the United States is approximately 30% of the total value of the inventory. That means if a company has $10 million worth of products in inventory, the cost of holding the inventory (including insurance, obsolescence, depreciation, interest, opportunity costs, storage costs, and so on) is approximately $3 million. If inventory could be reduced by half, to $5 million, then $1.5 million would be saved, a significant cost reduction.
The high cost of inventory has motivated companies to focus on efficient supply chain management and quality management. They believe that inventory can be significantly reduced by reducing uncertainty at various points along the supply chain. In many cases, uncertainty is created by poor quality on the part of the company or its suppliers or both. This can be in the form of variations in delivery times, uncertain production schedules caused by late deliveries, or large numbers of defects that require higher levels of production or service than what should be necessary, large fluctuations in customer demand, or poor forecasts of customer demand.
With efficient supply chain management, products or services are moved from one stage in the supply chain to the next according to a system of constant communication between customers and suppliers. Items are replaced as they are diminished without maintaining larger buffer stocks of inventory at each stage to compensate for late deliveries, inefficient service, poor quality, or uncertain demand. An efficient, well-coordinated supply chain reduces or eliminates these types of uncertainty so that this type of system will work.
Some companies maintain in-process, buffer inventories between production stages to offset irregularities and problems and keep the supply chain flowing smoothly. Quality-oriented companies consider large buffer inventories to be a costly crutch that masks problems and inefficiency primarily caused by poor quality. Adherents of quality management believe that inventory should be minimized. However, this works primarily for a production or manufacturing process. For the retailer who sells finished goods directly to the consumer or the supplier who sells parts or materials to the manufacturer, inventory is a necessity. Few shoe stores, discount stores, or department stores can stay in business with only one or two items on their shelves or racks. For these supply chains the traditional inventory decisions of how much to order and when to order continue to be important. In addition, the traditional approaches to inventory management are still widely used by most companies.
In this chapter we review the basic elements of traditional inventory management and discuss several of the more popular models and techniques for making cost-effective inventory decisions. These decisions are basically how much to order and when to order to replenish inventory to an optimal level.
Despite quality management's (QM) goal to minimize inventory, it's still required for retailers and suppliers.
THE ROLE OF INVENTORY IN SUPPLY CHAIN MANAGEMENT
A company employs an inventory strategy for many reasons. The main reason is holding inventories of finished goods to meet customer demand for a product, especially in a retail operation. However, customer demand can also be a secretary going to a storage closet to get a printer cartridge or paper, or a carpenter getting a board or nails from a storage shed.
Since demand is usually not known with certainty, it is not possible to produce exactly the amount demanded. An additional amount of inventory, called safety, or buffer, stocks, is kept on hand to meet variations in product demand. In the bullwhip effect (which we have discussed previously in our chapters on supply chain and forecasting), demand information is distorted as it moves away from the end-use customer. This uncertainty about demand back upstream in the supply chain causes distributors, manufacturers, and suppliers to stock increasingly higher safety stock inventories to compensate.
Additional stocks of inventories are sometimes built up to meet demand that is seasonal or cyclical. Companies will continue to produce items when demand is low to meet high seasonal demand for which their production capacity is insufficient. For example, toy manufacturers produce large inventories during the summer and fall to meet anticipated demand during the holiday season. Doing so enables them to maintain a relatively smooth supply chain flow throughout the year. They would not normally have the production capacity or logistical support to produce enough to meet all of the holiday demand during that season. In the same way retailers might find it necessary to keep large stocks of inventory on their shelves to meet peak seasonal demand, or for display purposes to attract buyers.
At the other end of the supply chain from finished goods inventory, a company might keep large stocks of pans and material inventory to meet variations in supplier deliveries. Inventory provides independence from vendors that a company does not have direct control over. Inventories of raw materials and purchased parts are kept on hand so that the production process will not be delayed as a result of missed or late deliveries or shortages from a supplier.
A company will purchase large amounts of inventory to take advantage of price discounts, as a hedge against anticipated price increases in the future, or because it can get a lower price by purchasing in volume. Walmart stores have been known to purchase a manufacturer's entire stock of soap powder or other retail item because they can get a very low price, which they subsequently pass on to their customers. Companies purchase large stocks of low-priced items when a supplier liquidates. In some cases, large orders will be made simply because the cost of ordering may be very high, and it is more cost-effective to have higher inventories than to order frequently.
Many companies find it necessary to maintain buffer inventories at different stages of their production process to provide independence between stages and to avoid work stoppages or delays. Inventories are kept between stages in the manufacturing process so that production can continue smoothly if there are temporary machine breakdowns or other work stoppages. Similarly, a stock of finished parts or products allows customer demand to be met in the event of a work stoppage or problem with transportation or distribution.
Inventory is kept between stages of a production process.
THE EFFECTS OF INFORMATION TECHNOLOGY ON INVENTORY MANAGEMENT
As we pointed out in previous chapters, information technology (IT) has become an enabler for effective supply chain management. Traditionally inventory was owned by the buyer (as opposed to the supplier), it was kept at the buyer's location, and the buyer controlled how and when its inventory was replenished. However, in recent years these traditional aspects of inventory management have changed, due in large part to advances in IT. Because of technology and software—including such IT tools as enterprises resource planning (ERP) systems (including forecasting software), barcodes, radio frequency identification (RFID, and point-of-sales data—companies can track and locate inventory throughout its supply chain, which enables them to locate inventory somewhere other than their own facility, and control it remotely or have someone else control it. These technologies have enabled modern supply chain management practices such as vendor managed inventory (VMI), continuous replenishment programs (CRP), supplier hubs, and outsourcing operations to third-party service providers (3PL). In these practices inventory can be located at the supplier's facility, at the buyer's, or somewhere in between. Unlike traditional practices, the supplier owns inventory until the buyer needs it and it is delivered, thus relieving the buyer of inventory costs; order sizes are reduced, deliveries (which the supplier pays for) are increased, and the buyer avoids maintaining storage facilities. However, for this to be effective the supplier must be able to minimize its own inventory costs and optimize its own supply chain, which can be achieved if the buyer shares end-use demand and sales data with its suppliers through IT. This enables suppliers to make replenishment decisions and provide inventory to the buyer, as it's needed. A recent supply chain management practice is for inventory to be located at “supplier hubs” that are usually at, or in very close proximity to. the buyer, and are often owned and operated by a 3PL provider, which shifts all responsibility and liability for inventory to the suppliers that share the hub. For a supplier hub to work, the supply chain members—buyers, suppliers, and 3PL providers—must share information through information technology. The 3PL provider uses information provided by the buyer and suppliers (including forecasts and sales data) to consolidate shipping among suppliers, plan and execute all logistics, connect and coordinate all supply chain members through an IT system, and operate the hub facility. Supplier hubs are being used successfully by such companies as Dell, Apple, Fiat, Hewlett-Packard, Nokia, Cisco. Sam's Club, Samsung, and Volkswagen.
Inventory must be sufficient to provide high-quality customer service in QM.
INVENTORY AND QUALITY MANAGEMENT IN THE SUPPLY CHAIN
A company maintains inventory to meet its own demand and its customers' demand for items in the supply chain. The ability to meet effectively internal organizational demand or external customer demand in a timely, efficient manner is referred to as the level of customer service. A primary objective of supply chain management is to provide as high a level of customer service in terms of on-time delivery as possible. This is especially important in today's highly competitive business environment, where quality is such an important product characteristic. Customers for finished goods usually perceive quality service as availability of goods they want when they want them. (This is equally true of internal customers, such as company departments or employees.) To provide this level of quality customer service, the tendency is to maintain large stocks of all types of items. However, there is a cost associated with carrying items in inventory, which creates a cost tradeoff between the quality level of customer service and the cost of that service.
As the level of inventory increases to provide better customer service, inventory costs increase, whereas quality-related customer service costs, such as lost sales and loss of customers, decrease. The conventional approach to inventory management is to maintain a level of inventory that reflects a compromise between inventory costs and customer service. However, according to the contemporary “zero defects” philosophy of quality management, the long-term benefits of quality in terms of larger market share outweigh lower short-term production-related costs, such as inventory costs. Attempting to apply this philosophy to inventory management is not simple because one way of competing in today's diverse business environment is to reduce prices through reduced inventory costs.
THE ELEMENTS OF INVENTORY MANAGEMENT
Inventory is a stock of items kept by an organization to meet internal or external customer demand. Virtually every type of organization maintains some form of inventory. Department stores and grocery stores carry inventories of all the retail products they sell; a nursery has inventories of different plants, trees, and flowers; a rental-car agency has inventories of cars; and a major league baseball team maintains an inventory of players on its minor league teams. Even a family household maintains inventories of items such as food, clothing, medical supplies, and personal hygiene products.
• Inventory: a stock of items kept to meet demand.
Most people think of inventory as a final product waiting to be sold to a retail customer—a new car or a can of tomatoes. This is certainly one of its most important uses. However, especially in a manufacturing firm, inventory can take on forms besides finished goods, including:
• Raw materials
• Purchased parts and supplies
• Partially complete work in progress (WIP)
• Items being transported
• Tools, and equipment
The purpose of inventory management is to determine the amount of inventory to keep in stock—how much to order and when to replenish, or order. In this chapter we describe several different inventory systems and techniques for making these determinations.
Inventory management: how much and when to order.
DEMAND
The starting point for the management of inventory is customer demand. Inventory exists to meet customer demand. Customers can be inside the organization, such as a machine operator waiting for a part or partially completed product to work on. Customers can also be outside the organization—for example, an individual purchasing groceries or a new DVD player. In either case, an essential determinant of effective inventory management is an accurate forecast of demand. For this reason the topics of forecasting (Chapter 12) and inventory management are directly interrelated.
In general, the demand for items in inventory is either dependent or independent. Dependent demand items are typically component parts or materials used in the process of producing a final product. If an automobile company plans to produce 1000 new cars, then it will need 5000 wheels and tires (including spares). The demand for wheels is dependent on the production of cars—the demand for one item depends on demand for another item.
• Dependent demand: items are used internally to produce a final product.
Cars, retail items, grocery products, and office supplies are examples of independent demand items. Independent demand items are final or finished products that are not a function of, or dependent on, internal production activity. Independent demand is usually determined by external market conditions and. thus, is beyond the direct control of the organization. In this chapter we focus on the management of inventory for independent demand items.
• Independent demand: items are final products demanded by external customers.
INVENTORY COSTS
Three basic costs are associated with inventory: carrying, or holding, costs; ordering costs; and shortage costs.
Inventory costs: carrying, ordering, and shortage costs.
These offloaded cars at a port are an example of independent demand, as are appliances, computers, and houses. The tires on these cars are an example of an dependent demand item.
Carrying costs are the costs of holding items in inventory. Annual inventory carrying costs in the United States are estimated to be over $300 billion. These costs vary with the level of inventory in stock and occasionally with the length of time an item is held. That is, the greater the level of inventory over a period of time, the higher the carrying costs. In general, any cost that grows linearly with the number of units in stock is a carrying cost. Carrying costs can include the following items:
•Carrying costs: the costs of holding an item in inventory.
• Facility storage (rent, depreciation, power, heat, cooling, lighting, security, refrigeration, taxes, insurance, etc.)
• Material handling (equipment)
• Labor
• Record keeping
• Borrowing to purchase inventory (interest on loans, taxes, insurance)
• Product deterioration, spoilage, breakage, obsolescence, pilferage
Carrying costs are normally specified in one of two ways. The usual way is to assign total carrying costs, determined by summing all the individual costs just mentioned, on a per-unit basis per time period, such as a month or year. In this form, carrying costs are commonly expressed as a per-unit dollar amount on an annual basis; for example. $10 per unit per year. Alternatively, carrying costs are sometimes expressed as a percentage of the value of an item or as a percentage of average inventory value. It is generally estimated that carrying costs range from 10 to 40% of the value of a manufactured item.
Carrying costs can range from 10 to 40% of the value of a manufactured item.
Ordering costs are the costs associated with replenishing the stock of inventory being held. These are normally expressed as a dollar amount per order and are independent of the order size. Annual ordering costs vary with the number of orders made—as the number of orders increases, the ordering cost increases. In general, any cost that increases linearly with the number of orders is an ordering cost. Costs incurred each time an order is made can include requisition and purchase orders, transportation and shipping, receiving, inspection, handling, and accounting and auditing costs.
• Ordering costs: the costs of replenishing inventory.
Ordering costs react inversely to carrying costs. As the size of orders increases, fewer orders are required, reducing ordering costs. However, ordering larger amounts results in higher inventory levels and higher carrying costs. In general, as the order size increases, ordering costs decrease and carrying costs increase.
Shortage costs , also referred to as stockout costs, occur when customer demand cannot be met because of insufficient inventory. If these shortages result in a permanent loss of sales, shortage costs include the loss of profits. Shortages can also cause customer dissatisfaction and a loss of goodwill that can result in a permanent loss of customers and future sales. Some studies have shown that approximately 8% of shoppers will not find the product they want to purchase in stock, which will ultimately result in total lost sales of about 3%.
•Shortage costs: temporary or permanent loss of sales when demand cannot be met.
In some instances, the inability to meet customer demand or lateness in meeting demand results in penalties in the form of price discounts or rebates. When demand is internal, a shortage can cause work stoppages in the production process and create delays, resulting in downtime costs and the cost of lost production (including indirect and direct production costs).
Costs resulting from lost sales because demand cannot be met are more difficult to determine than carrying or ordering costs. Therefore, shortage costs are frequently subjective estimates and sometimes an educated guess.
Shortages occur because carrying inventory is costly. As a result, shortage costs have an inverse relationship to carrying costs—as the amount of inventory on hand increases, the carrying cost increases, whereas shortage costs decrease.
The objective of inventory management is to employ an inventory control system that will indicate how much should be ordered and when orders should take place so that the sum of the three inventory costs just described will be minimized.
INVENTORY CONTROL SYSTEMS
An inventory system controls the level of inventory by determining how much to order (the level of replenishment) and when to order. There are two basic types of inventory systems: a continuous (or fixed-order-quantity) system and a periodic (or fixed-lime-period) system. In a continuous system, an order is placed for the same constant amount whenever the inventory on hand decreases to a certain level, whereas in a periodic system, an order is placed for a variable amount after specific regular intervals.
CONTINUOUS INVENTORY SYSTEMS
In a continuous inventory system (also referred to as a perpetual system and a fixed-order-quantity system), a continual record of the inventory level for every item is maintained. Whenever the inventory on hand decreases to a predetermined level, referred to as the reorder point, a new order is placed to replenish the stock of inventory. The order that is placed is for a fixed amount that minimizes the total inventory costs. This amount, called the economic order quantity, is discussed in greater detail later.
• Continuous inventory system: a constant amount is ordered when inventory declines to a predetermined level.
A positive feature of a continuous system is that the inventory level is continuously monitored, so management always knows the inventory status. This is advantageous for critical items such as replacement parts or raw materials and supplies. However, maintaining a continual record of the amount of inventory on hand can also be costly.
A simple example of a continuous inventory system is a ledger-style checkbook that many of us use on a daily basis. Our checkbook comes with 300 checks; after the 200th check has been used (and there are 100 left), there is an order form for a new batch of checks. This form, when turned in at the bank, initiates an order for a new batch of 300 checks. Many office inventory systems use reorder cards that are placed within stacks of stationery or at the bottom of a case of pens or paper clips to signal when a new order should be placed. If you look behind the items on a hanging rack in a Kmart store, there will be a card indicating it is time to place an order for the item for an amount indicated on the card.
Continuous inventory systems often incorporate information technology tools to improve the speed and accuracy of data entry. A familiar example is the computerized checkout system with a laser scanner used by many supermarkets and retail stores. The laser scanner reads the universal product code (UPC), or bar code, from the product package; the transaction is instantly recorded, and the inventory level updated. Such a system is not only quick and accurate, it also provides management with continuously updated information on the status of inventory levels. Many manufacturing companies' suppliers and distributors also use bar code systems and handheld laser scanners to inventory materials, supplies, equipment, in-process parts, and finished goods.
To consumers the most familiar type of bar code scanners are used with cash registers at retail stores, where the bar code is a single tine with 11 digits, the first 6 identifying a manufacturer and the last 5 assigned to a specific product by the manufacturer. This employee is using a portable hand held bar code scanner to scan a bar code for inventory control. In addition to identifying the product, it can indicate where a product came from, where it is supposed to go, and how the product should be handled in transit.
PERIODIC INVENTORY SYSTEMS
In a periodic inventory system (also referred to as a fixed-time-period system or a periodic review system), the inventory on hand is counted at specific time intervals—for example, every week or at the end of each month. After the inventory in stock is determined, an order is placed for an amount that will bring inventory back up to a desired level. In this system, the inventory level is not monitored at all during the time interval between orders, so it has the advantage of little or no required record keeping. The disadvantage is less direct control. This typically results in larger inventory levels for a periodic inventory system than in a continuous system to guard against unexpected stockouts early in the fixed period. Such a system also requires that a new order quantity be determined each time a periodic order is made.
• Periodic inventory system: an order is placed for a variable amount after a fixed passage of fine.
An example of a periodic inventory system is a college or university bookstore. Textbooks are normally ordered according to a periodic system, wherein a count of textbooks in stock (for every course) is made after the first few weeks of a semester or quarter. An order for new textbooks for the next semester is then made according to estimated course enrollments for the next term (i.e., demand) and the amount remaining in stock. Smaller retail stores, drugstores, grocery stores, and offices sometimes use periodic systems—the stock level is checked every week or month, often by a vendor, to see how much should be ordered.
THE ABC CLASSIFICATION SYSTEM
The ABC system is a method for classifying inventory according to several criteria, including its dollar value to the firm. Typically, thousands of independent demand items are held in inventory by a company, especially in manufacturing, but a small percentage is of such a high dollar value to warrant close inventory control. In general, about 5 to 15% of all inventory items account for 70 to 80% of the total dollar value of inventory. These are classified as A, or Class A, items. B items represent approximately 30% of total inventory units but only about 15% of total inventory dollar value. C items generally account for 50 to 60% of all inventory units but represent only 5 to 10% of total dollar value. For example, a discount store such as Walmart normally stocks a relatively small number of televisions, a somewhat larger number of bicycles or sets of sheets, and hundreds of boxes of soap powder, bottles of shampoo, and AA batteries. Figure 13.1 shows the approximate ABC classes.
•ABC system: an inventory classification system in which a small percentage of [A] items account for most of the inventory value.
In ABC analysis each class of inventory requires different levels of inventory monitoring and control—the higher the value of the inventory, the tighter the control. Class A items should experience tight inventory control; B and C require more relaxed (perhaps minimal) attention. However, the original rationale for ABC analysis was that continuous inventory monitoring was expensive and not justified for many items. The wide use of bar code scanners may have eroded that reasoning. At least for larger companies, bar codes have made continuous monitoring cheap enough to use for all item classes.
ALONG THE SUPPLY CHAIN Inventory Management at Dell
Dell Inc., has annual revenues of approximately $58 billion and over 75.000 employees around the world. Dell's business model bypasses retailers, and it sells directly to customers via phone or the Internet. This eliminates one major stage in its supply chain and the associated delays and costs. In Dell's supply chain, once a customer places an order (by phone or via the Internet) a credit check is made and the technical feasibility of the computer configuration is checked, a process that takes two or three days. After an order is processed through these initial steps, it is sent to one of its assembly plants in Austin, Texas, where the product is built, tested, and packaged within eight hours. Dell carries very little components inventory itself. Technology changes occur so fast that holding inventory can be a huge liability; some components lose 0.5–2% of their value per week. In addition, many of Dell's suppliers are located in Southeast Asia and their shipping times to Austin range from seven days for air transport to 30 days for water and ground transport. To compensate for these factors Dell's suppliers keep inventory in small warehouses called “revolvers” (for revolving inventory), which are few miles from Dell's assembly plants. Dell keeps very little inventory at its own plants so it withdraws inventory from the revolvers every few hours while most of Dell's suppliers deliver to their revolvers three times per week. However, the cost of carrying inventory by Dell's suppliers is ultimately charged to Dell as part of the component price, and is thus reflected in the final price of a computer. In order to maintain a competitive price advantage in the market Dell strives to help its suppliers keep inventory low and reduce inventory costs. Dell has a vendor managed inventory (VMI) arrangement with its suppliers. In this VMI system the suppliers decide how much to order and when to send their orders to the revolvers. Dell's suppliers order in batches (to offset ordering costs) using a continuous ordering system with a batch order size, Q, and a reorder point, R, where R is the sum of the inventory on order and a safety stock. The order size estimate, based on long-term data and forecasts, is held constant. Dell sets target inventory levels for its suppliers—typically 10 days of inventory—and keeps track of how much suppliers deviate from these targets and reports this information back to suppliers so that they can make adjustment accordingly.
Why do you think Dell holds the order size Q, constant in its continuous order system?
Source: R. Kapuscinski, R. Zhang, P. Carbonneau, R. Moore, and B. Reeves. “Inventory Decisions in Dell's Supply Chain,” Interfaces 34 (3; May–June 2004), pp. 191–205.
A items require close inventory control because of their high value: B and C items less control.
Figure 13.1 ABC Classifications
The first step in ABC analysis is to classify all inventory items as either A, B, or C. Each item is assigned a dollar value, which is computed by multiplying the dollar cost of one unit by the annual demand for that item. All items are then ranked according to their annual dollar value, with, for example, the top 10% classified as A items, the next 30% as B items, and the last 60% as C items. These classifications will not be exact, but they have been found to be close to the actual occurrence in firms with remarkable frequency.
A items require close inventory control because of their high value; B and C items less control.
The next step is to determine the level of inventory control for each classification. Class A items require tight inventory control because they represent such a large percentage of the total dollar value of inventory. These inventory levels should be as low as possible, and safety stocks minimized. This requires accurate demand forecasts and detailed record keeping. The appropriate inventory control system and inventory modeling procedure to determine order quantity should be applied. In addition, close attention should be given to purchasing policies and procedures if the inventory items are acquired from outside the firm. B and C items require less stringent inventory control. Since carrying costs are usually lower for C items, higher inventory levels can sometimes be maintained with larger safety stocks. It may not be necessary to control C items beyond simple observation. In general, A items frequently require a continuous control system, where the inventory level is continuously monitored; a periodic review system with less monitoring will suffice for C items.
Although cost is the predominant reason for inventory classification, other factors such as scarcity of parts or difficulty of supply may also be reasons for giving items a higher priority. For example, long lead times for some parts might be a problem for a company in Australia ordering from Europe, thus requiring a higher-priority classification for those parts.
Example 13.1 ABC System Classification
The maintenance department for a small manufacturing firm has responsibility for maintaining an inventory of spare parts for the machinery it services. The parts inventory, unit cost, and annual usage are as follows:
Part
Unit Cost
Annual Usage
1
$ 60
90
2
350
40
3
30
130
4
80
60
5
30
100
6
20
180
7
10
170
8
320
50
9
510
60
10
20
120
The department manager wants to classify the inventory parts according to the ABC system to determine which stocks of parts should most closely be monitored.
Solution
First rank the items according to their total value and also compute each item's percentage of total value and quantity.
Based on simple observation, it appears that the first three items form a group with the highest value, the next three items form a second group, and the last four items constitute a group. Thus, the ABC classification for these items is as follows:
Class
Items
%of Total Value
% of Total Quantity
A
9, 8, 2
71.0
15.0
B
1, 4, 3
16.5
28.0
C
6, 5, 10, 7
12.5
57.0
ALONG THE SUPPLY CHAIN Determining Supply Chain Strategy by Evaluating Inventory Costs at Hewlett-Packard
Hewlett-Packard, with annual revenues exceeding $90 billion and 150,000 employees worldwide, is the Fortune 500 eleventh-ranked company. Although demand for PCs increased by fivefold in the 1990s. becoming a veritable household product, many PC companies struggled to remain profitable. By the end of the 1990s HP was struggling to make a profit in the increasingly competitive global PC market because of price cuts throughout the 1990s. Since prices were not really controllable, inventory costs became especially critical in the PC profit equation. Rapid technological advancements render new PC products obsolete in a few months, and, in general, it's believed that the value of a PC decreases at the rate of 1% per week. As such, holding any excess inventory was very costly.
In the late 1990s, in order to return its PC business to more sustainable profitability, HP undertook an extensive evaluation of its supply chain costs. It discovered that inventory-related costs were the main determinants of overall PC cost, and, in fact, in one year alone inventory-related costs equaled the PC business's total operating margin. Further, HP determined that the traditional inventory carrying (or holding) costs (which encompasses capital costs plus, storage, taxes, insurance, breakage, etc.), accounted for less than 10% of the total inventory-related costs. HP identified four additional inventory costs in their PC business that were a major factor in overall supply chain costs. The single biggest inventory cost was determined to be the “component devaluation cost.” This is the penalty cost HP incurred when the price dropped for excess components and parts (e.g., CPUs, memory, and chips) being held in inventory. HP held inventories of parts and components in factories, in distribution centers, and in transit, and would incur a devaluation cost at all of these points in its supply chain whenever a price reduction occurred. Another inventory cost is the “price protection cost,” which occurs when the retail price of a product drops after it has already been shipped to the sales outlet. HP has to reimburse its sales partners for the difference in price for any unsold units, so its partners won't incur a loss. Given how fast PC products lose their value, excess inventory can result in large protection costs. A third inventory-related cost in the PC business is the “product return cost.” This is the cost of a full refund HP pays its distributors when unsold products are returned; essentially it is a 100% price protection cost. In some cases sales partners and distributors returned excess unsold inventory valued at more than 10% of a product's revenue. The fourth inventory cost is “obsolescence cost,” which is the cost of writing-off unsold products in inventory after the life of the product ends. Since PC products lifecycles are so short, there is the potential for large costs if excessive inventories are held. Related costs include price discounts for products that are about to be discontinued and the marketing costs to quickly reduce inventory. The Mobile Computing Division (that manufactures notebooks) was the first HP PC business unit to focus on all of these inventory-related costs in redesigning its supply chain. The original supply chain consisted of a central manufacturing facility with local product configuration occurring at regional sites. (In this configuration about 40% of the total supply chain cost was related to inventory). In the redesigned supply chain there is a central manufacturing facility and products are air freighted directly to customers around the world. Positive results were immediate; in a two-year period inventory-related costs dropped from almost 19% of total revenue to less than 4%, and the notebook division became profitable. As a result, all other HP PC operations began using these inventory costs to evaluate and redesign their supply chains.
Hewlett-Packard seems to incur some inventory costs that Dell with its vendor managed inventory (VMI) system (see page 503) does not. Compare the two different supply chain designs for these major computer manufacturers and discuss the advantages and disadvantages of each.
Source: G. Callioni, X. de Montgros, R. Slagmulder, L. N. Van Wassenhove, and L. Wright, “Inventory-Driven Costs.” The Harvard Business Review 83 (3; March 2005), pp. 135–141.
ECONOMIC ORDER QUANTITY MODELS
In a continuous, or fixed-order-quantity, system when inventory reaches a specific level, referred to as the reorder point, a fixed amount is ordered. The most widely used and traditional means for determining how much to order in a continuous system is the economic order quantity (EOQ) model, also referred to as the economic lot-size model. The earliest published derivation of the basic EOQ model formula in 1915 is credited to Ford Harris, an employee at Westinghouse.
• Economic order quantity (EOQ): the optimal order quantity that will minimize total inventory costs.
The function of the EOQ model is to determine the optimal order size that minimizes total inventory costs. There are several variations of the EOQ model, depending on the assumptions made about the inventory system. We will describe two model versions: the basic EOQ model and the production quantity model.
THE BASIC EOQ MODEL
The basic EOQ model is a formula for determining the optimal order size that minimizes the sum of carrying costs and ordering costs. The model formula is derived under a set of simplifying and restrictive assumptions, as follows:
Assumptions of EOQ model
• Demand is known with certainty and is constant over time.
• No shortages are allowed.
• Lead time for the receipt of orders is constant.
• The order quantity is received all at once.
These basic model assumptions are reflected in Figure 13.2, which describes the continuous-inventory order cycle system inherent in the EOQ model. An order quantity, Q, is received and is used up over time at a constant rate. When the inventory level decreases to the reorder point, R, a new order is placed; a period of time, referred to as the lead time, is required for delivery. The order is received all at once just at the moment when demand depletes the entire stock of inventory—the inventory level reaches 0—so there will be no shortages. This cycle is repeated continuously for the same order quantity, reorder point, and lead time.
• Order cycle: the time between receipt of orders in an inventory cycle.
EOQ is a continuous inventory system.
As we mentioned, the economic order quantity is the order size that minimizes the sum of carrying costs and ordering costs. These two costs react inversely to each other. As the order size increases, fewer orders are required, causing the ordering cost to decline, whereas the average amount of inventory on hand will increase, resulting in an increase in carrying costs. Thus, in effect, the optimal order quantity represents a compromise between these two inversely related costs.
Figure 13.2 The Inventory Order Cycle
The total annual ordering cost is computed by multiplying the cost per order, designated as Co, times the number of orders per year. Since annual demand. D, is assumed to be known and to be constant, the number of orders will be D/Q, where Q is the order size and
The only variable in this equation is Q; both Co and D are constant parameters. Thus, the relative magnitude of the ordering cost is dependent on the order size.
Total annual carrying cost is computed by multiplying the annual per-unit carrying cost, designated as Cc, multiplied by the average inventory level. The average inventory level is one-half of Q or Q/2, as shown in Figure 13.2.
The total annual inventory cost is the sum of the ordering and carrying costs:
The graph in Figure 13.3 shows the inverse relationship between ordering cost and carrying cost, resulting in a convex total cost curve.
Optimal Q corresponds to the lowest point on the total cost curve.
The optimal order quantity occurs at the point in Figure 13.3 where the total cost curve is at a minimum, which coincides exactly with the point where the carrying cost curve intersects the ordering cost curve. This enables us to determine the optimal value of Q by equating the two cost functions and solving for Q:
Figure 13.3 The EOQ Cost Model
Alternatively, the optimal value of Q can be determined by differentiating the total cost curve with respect to Q, setting the resulting function equal to zero (the slope at the minimum point on the total cost curve), and solving for Q:
The total minimum cost is determined by substituting the value for the optimal order size, Qopt, into the total cost equation:
Example 13.2 The Economic Order Quantity
The ePaint Store stocks paint in its warehouse and sells it online on its Internet Web site. The store stocks several brands of paint; however, its biggest seller is Sharman-Wilson Ironcoat paint. The company wants to determine the optimal order size and total inventory cost for Ironcoat paint given an estimated annual demand of 10,000 gallons of paint, an annual carrying cost of $0.75 per gallon, and an ordering cost of $150 per order. They would also like to know the number of orders that will be made annually and the time between orders (i.e., the order cycle).
Solution
The optimal order size is
The total annual inventory cost is determined by substituting Qopt into the total cost formula:
The number of orders per year is computed as follows:
Given that the company processes orders 311 days annually (365 days minus 52 Sundays, Thanksgiving, and Christmas), the order cycle is
The optimal order quantity, determined in this example, and in general, is an approximate value, since it is based on estimates of carrying and ordering costs as well as uncertain demand (although all of these parameters are treated as known, certain values in the EOQ model). In practice it is desirable to round the Q values off to some nearby pragmatic value. The precision of a decimal place is generally not necessary. In addition, because the optimal order quantity is computed from a square root, errors or variations in the cost parameters and demand tend to be dampened. For instance, in Example 13.2, if the order cost had actually been 30% higher, or $200, the resulting optimal order size would have varied only by a little under 10% (i.e., 2190 gallons instead of 2000 gallons). Variations in both inventory costs will tend to offset each other, since they have an inverse relationship. As a result, the EOQ model is relatively resilient to errors in the cost estimates and demand, or is robust, which has tended to enhance its popularity.
The EOQ model is robust; because Q is a square root, errors in the estimation of D, Cc. and Co are dampened.
THE PRODUCTION QUANTITY MODEL
A variation of the basic EOQ model is the production quantity model , also referred to as the gradual usage and non-instantaneous receipt model. In this EOQ model the assumption that orders are received all at once is relaxed. The order quantity is received gradually over time, and the inventory level is depleted at the same time it is being replenished. This situation is commonly found when the inventory user is also the producer, as in a manufacturing operation where a part is produced to use in a larger assembly. This situation also can occur when orders are delivered continuously over time or when a retailer is also the producer.
• Production quantity model: an inventory system in which an order is received gradually, as inventory is simultaneously being depleted.
Relaxing the assumption that Q is received all at once.
Figure 13.4 The Production Quantity Model
The noninstantaneous receipt model is shown graphically in Figure 13.4. The inventory level is gradually replenished as an order is received. In the basic EOQ model, average inventory was half the maximum inventory level, or Q/2, but in this model variation, the maximum inventory level is not simply Q; it is an amount somewhat lower than Q, adjusted for the fact the order quantity is depleted during the order receipt period.
In order to determine the average inventory level, we define the following parameters unique to this model:
p = daily rate at which the order is received over time, also known as the production rate
d = the daily rate at which inventory is demanded
The demand rate cannot exceed the production rate, since we are still assuming that no shortages are possible, and, if d = p, there is no order size, since items are used as fast as they are produced. For this model the production rate must exceed the demand rate, or p ≥ d.
Observing Figure 13.4 we see that the time required to finish receiving an order is the order quantity divided by the rate at which the order is received, or Q/p. For example, if the order size is 100 units and the production rate, p, is 20 units per day. the order will be received over five days. The amount of inventory that will be depleted or used up during this time period is determined by multiplying by the demand rate: (Q/p)d. For example, if it takes five days to receive the order and during this time inventory is depleted at the rate of two units per day, then 10 units are used. As a result, the maximum amount of inventory on hand is the order size minus the amount depleted during the receipt period, computed as
Since this is the maximum inventory level, the average inventory level is determined by dividing this amount by 2:
The total carrying cost using this function for average inventory is
In this case the ordering cost, Co, is often the setup cost for production.
Thus, the total annual inventory cost is determined according to the following formula:
Solving this function for the optimal value Q,
Example 13.3 The Production Quantity Model
Assume that the ePaint Store has its own manufacturing facility in which it produces Ironcoat paint. The ordering cost, Co, is the cost of setting up the production process to make paint. C o = $150. Recall that Cc = $0.75 per gallon and D = 10,000 gallons per year. The manufacturing facility operates the same days the store is open (i.e., 311 days) and produces 150 gallons of paint per day. Determine the optimal order size, total inventory cost, the length of time to receive an order, the number of orders per year, and the maximum inventory level.
Solution
The optimal order size is determined as follows:
Although an order of 2256.8 gallons should be rounded to 2257, we will use the 2256.8 to compute total cost.
This value is substituted into the following formula to determine total minimum annual inventory cost:
The length of time to receive an order for this type of manufacturing operation is commonly called the length of the production run.
The number of orders per year is actually the number of production runs that will be made:
Finally, the maximum inventory level is
Thus, ePaint will need to set aside storage space sufficient to accommodate these 1772 gallons of paint.
SOLUTION OF EOQ MODELS WITH EXCEL
EOQ analysis can be done with Excel. The Excel solution screen for Example 13.2 is shown in Exhibit 13.1. The Excel screen for the production quantity model in Example 13.3 is shown in Exhibit 13.2.
Exhibit 13.1
• Excel File
Exhibit 13.2
• Excel File
SOLUTION OF EOQ MODELS WITH OM TOOLS
OM tools has modules to solve all the various inventory models illustrated in this chapter, including the ABC model for Example 13.1, the EOQ, and production quality models for Examples 13.2 and 13.3. the quantity discount model (Example 13.4), the recorder point model (Examples 13.5 and 13.6), and the fixed-period model (Example 13.7). As an example, Exhibit 13.3 shows the OM Tools spreadsheet for the EOQ Model in Example 13.2.
Exhibit 13.3
• OM Tools File
QUANTITY DISCOUNTS
A quantity discount is a price discount on an item if predetermined numbers of units are ordered. In the back of a magazine you might see an advertisement for a firm stating that it will produce a coffee mug (or hat) with a company or organizational logo on it, and the price will be $5 per mug if you purchase 100, $4 per mug if you purchase 200, or $3 per mug if you purchase 500 or more. Many manufacturing companies receive price discounts for ordering materials and supplies in high volume, and retail stores receive price discounts for ordering merchandise in large quantities.
• Quantity discount: given for specific higher order quantities.
The basic EOQ model can be used to determine the optimal order size with quantity discounts; however, the application of the model is slightly altered. The total inventory cost function must now include the purchase price of the item being ordered:
where
Purchase price was not considered as part of our basic EOQ formulation earlier because it had no impact on the optimal order size. In the preceding formula PD is a constant value that would not alter the basic shape of the total cost curve; that is, the minimum point on the cost curve would still be at the same location, corresponding to the same value of Q. Thus, the optimal order size is the same no matter what the purchase price is. However, when a discount price is available, it is associated with a specific order size, which may be different from the optimal order size, and the customer must evaluate the tradeoff between possibly higher carrying costs with the discount quantity versus EOQ cost. As a result, the purchase price does affect the order-size decision when a discount is available.
QUANTITY DISCOUNTS WITH CONSTANT CARRYING COST
The EOQ cost model with constant carrying costs for a pricing schedule with two discounts, d1 and d2, is illustrated in Figure 13.5 for the following discounts:
Determining if an order size with a discount is more cost effective than optimal Q.
Figure 13.5 Quantity Discounts with Constant Carrying Cost
Notice in Figure 13.5 that the optimal order size, Qopt, is the same regardless of the discount price. Although the total cost curve decreases with each discount in price (i.e., d1 and d2), since ordering and carrying cost are constant, the optimal order size, Qopt, does not change.
The graph in Figure 13.5 reflects the composition of the total cost curve resulting from the discounts kicking in at two successively higher order quantities. The first segment of the total cost curve (with no discount) is valid only up to 99 units ordered. Beyond that quantity, the total cost curve (represented by the topmost dashed line) is meaningless because above 100 units there is a discount (d1). Between 100 and 199 units the total cost drops down to the middle curve. This middle-level cost curve is valid only up to 199 units because at 200 units there is another, lower discount (d2). So the total cost curve has two discrete steps, starting with the original total cost curve, dropping down to the next level cost curve for the first discount, and finally dropping to the third-level cost curve for the final discount.
Notice that the optimal order size, Qopt, is feasible only for the middle level of the total cost curve, TC(d1)—it does not coincide with the top level of the cost curve, TC, or the lowest level, TC(d2). If the optimal EOQ order size had coincided with the lowest level of the total cost curve, TC(d2), it would have been optimal order size for the entire discount price schedule. Since it does not coincide with the lowest level of the total cost curve, the total cost with Qopt must be compared to the lower-level total cost using Q(d2) to see which results in the minimum total cost. In this case the optimal order size is 200.
Example 13.4 A Quantity Discount with Constant Carrying Cost
Avtek, a distributor of audio and video equipment, wants to reduce a large stock of televisions. It has offered a local chain of stores a quantity discount pricing schedule, as follows:
Quantity
Price
1–49
$1400
50–89
1100
90+
900
The annual carrying cost for the stores for a TV is $190, the ordering cost is $2,500, and annual demand for this particular model TV is estimated to be 200 units. The chain wants to determine if it should take advantage of this discount or order the basic EOQ order size.
Solution
First determine the optimal order size and total cost with the basic EOQ model.
Although we will use Qopt = 72.5 in the subsequent computations, realistically the order size would be 73 televisions. This order size is eligible for the first discount of $1100; therefore, this price is used to compute total cost:
Since there is a discount for a larger order size than 50 units (i.e., there is a lower cost curve), this total cost of $233,784 must be compared with total cost with an order size of 90 and a discounted price of $900:
Since this total cost is lower ($194,105 < $233,784), the maximum discount price should be taken, and 90 units should be ordered. We know that there is no order size larger than 90 that would result in a lower cost, since the minimum point on this total cost curve has already been determined to be 73.
QUANTITY DISCOUNT MODEL SOLUTION WITH EXCEL
It is also possible to use Excel to solve the quantity-discount model with constant carrying cost. Exhibit 13.4 shows the Excel solution screen for Example 13.4. Notice that the selection of the appropriate order size. Q, that results in the minimum total cost for each discount range is determined by the formulas embedded in cells, E8, E9, and E10. For example, the formula for the first quantity-discount range, “1–49,” is embedded in cell E8 and shown on the formula bar at the top of the screen, “=IF(D8.= B8,D8,B8).” This means that if the discount order size in cell D8 (i.e., Q = 72.55) is greater than or equal to the quantity in cell B8 (i.e., 1), then the quantity in cell D8 (72.55) is selected; otherwise the amount in cell B8 is selected. The formulas in cells E9 and E10 are constructed similarly. The result is that the order quantity for the final discount range, Q = 90, is selected.
Exhibit 13.4
• Excel File
REORDER POINT
In our description of the EOQ models in the previous sections, we addressed how much should be ordered. Now we will discuss the other aspect of inventory management, when to order. The determinant of when to order in a continuous inventory system is the reorder point , the inventory level at which a new order is placed.
• Reorder point: the level of inventory at which a new order should be placed.
The reorder point for our basic EOQ model with constant demand and a constant lead time to receive an order is equal to the amount demanded during the lead time,
Example 13.5 Reorder Point for the Basic EOQ Model
The ePaint Internet Store in Example 13.2 is open 311 days per year. If annual demand is 10,000 gallons of Ironcoat paint and the lead time to receive an order is 10 days, determine the reorder point for paint.
Solution
When the inventory level falls to approximately 321 galloas of paint, a new order is placed. Notice that the reorder point is not related to the optimal order quantity or any of the inventory costs.
SAFETY STOCKS
In Example 13.5, an order is made when the inventory level reaches the reorder point. During the lead time, the remaining inventory in stock will be depleted at a constant demand rate, such that the new order quantity will arrive at exactly the same moment as the inventory level reaches zero. Realistically, demand—and, to a lesser extent lead time—are uncertain. The inventory level might be depleted at a faster rate during lead time. This is depicted in Figure 13.6 for uncertain demand and a constant lead time.
Notice in the second order cycle that a stockout occurs when demand exceeds the available inventory in stock. As a hedge against stockouts when demand is uncertain, a safety stock of inventory is frequently added to the expected demand during lead time. The addition of a safety stock to the stockout occurrence shown in Figure 13.6 is displayed in Figure 13.7.
• Stockout: an inventory shortage.
• Safety stock: a buffer added to the inventory on hand during lead time.
Figure 13.6 Variable Demand with a Reorder Point
SERVICE LEVEL
There are several ways to determine the amount of the safety stock. One popular method is to establish a safety stock that will meet a specified service level . The service level is the probability that the amount of inventory on hand during the lead time is sufficient to meet expected demand—that is, the probability that a stockout will not occur. The term service is used, since the higher the probability that inventory will be on hand, the more likely that customer demand will be met—that is, that the customer can be served. A service level of 90% means that there is a 0.90 probability that demand will be met during the lead time, and the probability that a stockout will occur is 10%. The service level is typically a policy decision based on a number of factors, including carrying costs for the extra safety stock and lost sales if customer demand cannot be met.
• Service level: the probability that the inventory available during lead time will meet demand.
REORDER POINT WITH VARIABLE DEMAND
To compute the reorder point with a safety stock that will meet a specific service level, we will assume the demand during each day of lead time is uncertain, independent, and can be described by a normal distribution. The average demand for the lead time is the sum of the average daily demand for the days of the lead time, which is also the product of the average daily demands multiplied by the lead time. Similarly, the variance of the distribution is the sum of the daily variances for the number of days in the lead time. Using these parameters, we can compute the reorder point to meet a specific service level as
The term in this formula for the reorder point is the square root of the sum of the daily-variances during lead time:
The reorder point relative to the service level is shown in Figure 13.8. The service level is the shaded area, or probability, to the left of the reorder point, R.
Figure 13.7 Reorder Point with a Safety Stock
Figure 13.8 Reorder Point for a Service Level
Example 13.6 Reorder Point for Variable Demand
For the ePaint Internet Store in Example 13.2, we will assume that daily demand for Ironcoat paint is normally distributed with an average daily demand of 30 gallons and a standard deviation of 5 gallons of paint per day. The lead time for receiving a new order of paint is 10 days. Determine the reorder point and safety stock if the store wants a service level of 95%—that is, the probability of a stockout is 5%.
Solution
For a 95% service level, the value of z (from the Normal table in Appendix A) is 1.65. The safety stock is:
The reorder point is computed as follows:
DETERMINING THE REORDER POINT WITH EXCEL
Excel can be used to determine the reorder point for variable demand. Exhibit 13.5 shows the Excel screen for Example 13.6. Notice that the reorder point is computed using the formula in cell E7, which is shown on the formula bar at the top of the screen.
Exhibit 13.5
• Excel File
ALONG THE SUPPLY CHAIN Establishing Inventory Safety Stocks at Kellogg's
Kellogg's is the world's largest cereal producer and a leading producer of convenience foods, with worldwide sales in 1999 of almost $7 billion. The company started with a single product, Kellogg's Corn Flakes, in 1906 and over the years developed a product line of other cereals including Rice Krispies and Corn Pops, and convenience foods such as Pop-Tarts and Nutri-Grain cereal bars. Kellogg's operates five plants in the United States and Canada and seven distribution centers, and it contracts with 15 co-packers to produce or pack some of Kellogg's products. Kellogg's must coordinate the production, packaging, inventory, and distribution of roughly 80 cereal products alone at these various facilities.
For more than a decade, Kellogg's has been using a model called the Kellogg Planning System (KPS) to plan its weekly production, inventory, and distribution decisions. The data used in the model is subject to much uncertainty, and the greatest uncertainty is in product demand. Demand in the first few weeks of a planning horizon is based on customer orders and is fairly accurate; however, demand in the third and fourth weeks may be significantly different from marketing forecasts. Kellogg's primary goal is to meet customer demand, and in order to achieve this goal Kellogg's employs safety stocks as a buffer against uncertain demand. The safety stock for a product at a specific production facility in week t is the sum of demands for weeks t and t + 1. However, for a product that is being promoted in an advertising campaign, the safety stock is the sum of forecasted demand for a four-week horizon or longer. KPS has saved Kellogg's many millions of dollars since the mid-1990s. The tactical version of KPS recently helped the company consolidate production capacity with estimated projected savings of almost $40 million.
The elimination or minimization of buffer stocks is typically a key strategic objective in supply chain design. Why do you think Kellogg's seems to accept that they are inevitable and necessary within their supply chain?
Source: G. Brown, J. Keegan, B. Vigus, and K. Wood, “The Kellogg Company Optimizes Production, Inventory, and Distribution,” Interfaces 31, no. 6 (November-December 2001), pp. 1–15.
ORDER QUANTITY FOR A PERIODIC INVENTORY SYSTEM
We defined a continuous, or fixed-order-quantity, inventory system as one in which the order quantity was constant and the time between orders varied. So far this type of inventory system has been the focus of our discussion. The less common periodic, or fixed-time-period, inventory system is one in which the time between orders is constant and the order size varies. Small retailers often use this sytem. Drugstores are one example of a business that sometimes uses a fixed-period inventory system. Drugstores stock a number of personal hygiene- and health-related products such as shampoo, toothpaste, soap, bandages, cough medicine, and aspirin.
Normally, the vendors who provide these items to the store will make periodic visits—every few weeks or every month—and count the stock of inventory on hand for their product. If the inventory is exhausted or at some predetermined reorder point, a new order will be placed for an amount that will bring the inventory level back up to the desired level. The drugstore managers will generally not monitor the inventory level between vendor visits but instead will rely on the vendor to take inventory.
A periodic inventory system normally requires a larger safety stock.
Under this system, the vendor would bundle many small, low-cost items into a single order and delivery thereby saving costs. Since the items are generally of low value, larger safety stocks will not pose a significant cost. Also, if the items are noncritical, even if there is a stockout, it is not a big deal. However, inventory might be exhausted early in the time period between visits, resulting in a stockout that will not be remedied until the next scheduled order. As a result, a larger safety stock for more critical items is sometimes required for the fixed-interval system.
Figure 13.9 Periodic Inventory System
ORDER QUANTITY WITH VARIABLE DEMAND
If the demand rate and lead time are constant, then the fixed-period model will have a fixed-order quantity that will be made at specified time intervals, which is the same as the fixed-quantity (EOQ) model under similar conditions. However, as we have already explained, the fixed-period model reacts differently than the fixed-order model when demand is a variable.
The order size for a fixed-period model given variable daily demand that is normally distributed is determined by
where
The first term in this formula, , is the average demand during the order cycle time plus the lead time. It reflects the amount of inventory that will be needed to protect against the entire time from this order to the next and the lead time until the order is received. The second term, , is the safety stock for a specific service level, determined in much the same way as previously described for a reorder point. These first two terms combined are a “target” level of inventory to maintain. The final term, I, is the amount of inventory on hand when the inventory level is checked and an order is made.
Figure 13.9 shows a periodic inventory system in which variable order sizes (Q) are placed at fixed time intervals (tb), and Example 13.7 on the following page illustrates this system.
DETERMINING THE ORDER QUANTITY FOR THE FIXED-PERIOD MODEL WITH EXCEL
The order quantity for the fixed-period model with variable demand can be determined using Excel. The Excel screen for Example 13.7 is shown in Exhibit 13.6. Notice that the order quantity in cell D10 is computed with the formula shown on the formula bar at the top of the screen.
Example 13.7 Order Size for Fixed-Period Model with Variable Demand
The KVS Pharmacy stocks a popular brand of over-the-counter flu and cold medicine. The average demand for the medicine is 6 packages per day, with a standard deviation of 1.2 packages. A vendor for the pharmaceutical company checks KVS's stock every 60 days. During one visit the store had 8 packages in stock. The lead time to receive an order is 5 days. Determine the order size for this order period that will enable KVS to maintain a 95% service level.
Solution
This will be rounded to 398 packages, or perhaps 400 if it is shipped in boxes of 100 packages.
Exhibit 13.6
• Excel File
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SUMMARY
The two types of systems for managing inventory are continuous and periodic, and we presented several models for determining how much to order and when to order for each system. However, we focused our attention primarily on the more commonly used continuous, fixed-order-quantity systems with EOQ models for determining order size and reorder points for determining when to order.
The objective of these order quantity models is to determine the optimal tradeoff between inventory carrying costs and ordering costs that would minimize total inventory cost.
However, a drawback of approaching inventory management in this manner is that it can delude management into thinking that if they determine the minimum cost order quantity, they have achieved all they can in reducing inventory costs, which is not the case. Management should continually strive both to accurately assess and to reduce individual inventory costs. If management has accurately determined carrying and order costs, then they can seek ways to lower them that will reduce overall inventory costs regardless of the order size and reorder point.
SUMMARY OF KEY FORMULAS
Basic EOQ Model
EOQ Model with Noninstantaneous Receipt
Inventory Cost for Quantity Discounts
Reorder Point with Constant Demand and Lead Time
Reorder Point with Variable Demand
Fixed-Time-Period Order Quantity with Variable Demand
SUMMARY OF KEY TERMS
ABC system
a method for classifying inventory' items according to their dollar value to the firm based on the principle that only a few items account for the greatest dollar value of total inventory.
carrying costs
the cost of holding an item in inventory, including lost opportunity costs, storage, rent, cooling, lighting, interest on loans, and so on.
continuous inventory system
a system in which the inventory level is continually monitored; when it decreases to a certain level, the reorder point, a fixed amount is ordered.
dependent demand
typically, component parts or materials used in the process to produce a final product.
economic order quantity (EOQ)
a fixed-order quantity that minimizes total inventory costs.
fixed-time-period system
also known as a periodic system; an inventory system in which a variable amount is ordered after a predetermined, constant passage of time.
independent demand
final or finished products whose demand is not a function of, or dependent on. internal production activity.
inventory
a stock of items kept by an organization to meet internal or external customer demand.
order cycle
the time between the receipt of orders in an inventory system.
ordering costs
the cost of replenishing the stock of inventory including requisition cost, transportation and shipping, receiving, inspection, handling, and so forth.
periodic inventory system
a system in which the inventory level is checked after a specific time period and a variable amount is ordered, depending on the inventory in stock.
production quantity model
also known as the production lot-size model; an inventory system in which an order is received gradually and the inventory level is depleted at the same time it is being replenished.
quantity discount
a pricing schedule in which lower prices are provided for specific (higher) order quantities.
reorder point
a level of inventory in stock at which a new order is placed.
safety Stock
an amount added to the expected amount demanded during the lead time (the reorder point level) as a hedge against a stockout.
service level
the probability that the amount of inventory on hand during the lead time is sufficient to meet expected demand.
shortage costs
temporary or permanent loss of sales that will result when customer demand cannot be met.
stockout an
inventory shortage occurring when demand exceeds the inventory in stock.
• Animated Demo Problem
SOLVED PROBLEMS
1. BASIC EOQ MODEL
Electronic Village stocks and sells a particular brand of personal computer. It costs the store $450 each time it places an order with the manufacturer for the personal computers. The annual cost of carrying the PCs in inventory is $170. The store manager estimates that annual demand for the PCs will be 1200 units. Determine the optimal order quantity and the total minimum inventory cost.
SOLUTION
2. PRODUCTION QUANTITY MODEL
I-75 Discount Carpels manufactures Cascade carpet, which it sells in its adjoining showroom store near the interstate. Estimated annual demand is 20,000 yards of carpet with an annual carrying cost of $2.75 per yard. The manufacturing facility operates the same 360 days the store is open and produces 400 yards of carpet per day. The cost of setting up the manufacturing process for a production run is $720. Determine the optimal order size, total inventory cost, length of time to receive an order, and maximum inventory level.
SOLUTION
3. QUANTITY DISCOUNT
A manufacturing firm has been offered a particular component part it uses according to the following discount pricing schedule provided by the supplier.
The manufacturing company uses 700 of the components annually, the annual carrying cost is $14 per unit, and the ordering cost is $275. Determine the amount the firm should order.
SOLUTION
First, determine the optimal order size and total cost with the basic EOQ model.
Next, compare the order size with the second-level quantity discount with an order size of 200 and a discount price of $59.
This discount results in a lower cost.
Finally, compare the current discounted order size with the fixed-price discount for Q = 600.
Since this total cost is higher, the optimal order size is 200 with a total cost of $43,662.50.
4. REORDER POINT WITH VARIABLE DEMAND
A computer products store stocks color graphics monitors, and the daily demand is normally distributed with a mean of 1.6 monitors and a standard deviation of 0.4 monitor. The lead time to receive an order from the manufacturer is 15 days. Determine the reorder point that will achieve a 98% service level.
SOLUTION
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QUESTIONS
13-1. Describe the difference between independent and dependent demand and give an example of each for a pizza restaurant such as Domino's or Pizza Hut.
13-2. Distinguish between a fixed-order-quantity system and fixed-time-period system and give an example of each.
13-3. Discuss customer service level for an inventory system within the context of quality management.
13-4. Explain the ABC inventory classification system and indicate its advantages.
13-5. Identify the two basic decisions addressed by inventory management and discuss why the responses to these decisions differ for continuous and periodic inventory systems.
13-6. Describe the major cost categories used in inventory analysis and their functional relationship to each other.
13-7. Explain how the order quantity is determined using the basic EOQ model.
13-8. What are the assumptions of the basic EOQ model, and to what extent do they limit the usefulness of the model?
13-9. How are the reorder point and lead lime related in inventory analysis?
13-10. Describe how the production quantity model differs from the basic EOQ model.
13-11. How must the application of the basic EOQ model be altered in order to reflect quantity discounts?
13-12. Why do the basic EOQ model variations not include the price of an item?
13-13. In the production quantity EOQ model, what would be the effect of the production rate becoming increasingly large as the demand rate became increasingly small, until the ratio d/p was negligible?
13-14. Explain in general terms how a safety stock level is determined using customer service level.
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PROBLEMS
13-1. AV City stocks and sells a particular brand of laptop. It costs the firm $625 each time it places an order with the manufacturer for the laptops. The cost of carrying one laptop in inventory for a year is $130. The store manager estimates that total annual demand for the laptops will be 1500 units, with a constant demand rate throughout the year. Orders are received within minutes after placement from a local warehouse maintained by the manufacturer. The store policy is never to have stockouts of the laptops. The store is open for business every day of the year except Christmas Day. Determine the following:
a. Optimal order quantity per order
b. Minimum total annual inventory costs
c. The number of orders per year
d. The time between orders (in working days)
13-2. AV City (Problem 13-1) assumed with certainty that the ordering cost is $625/order and the inventory carrying cost is $130/unit/year. However, the inventory model parameters are frequently only estimates that are subject to some degree of uncertainty. Consider four cases of variation in the model parameters as follows: (a) Both ordering cost and carrying cost are 10% less than originally estimated; (b) both ordering cost and carrying cost are 10% higher than originally estimated; (c) ordering cost is 10% higher and carrying cost is 10% lower than originally estimated; and (d) ordering cost is 10% lower and carrying cost is 10% higher than originally estimated. Determine the optimal order quantity and total inventory cost for each of the four cases. Prepare a table with values from all four cases and compare the sensitivity of the model solution to changes in parameter values.
13-3. A firm is faced with the attractive situation in which it can obtain immediate delivery of an item it stocks for retail sale. The firm has therefore not bothered to order the item in any systematic way. However, recently profits have been squeezed due to increasing competitive pressures, and the firm has retained a management consultant to study its inventory management. The consultant has determined that the various costs associated with making an order for the item stocked are approximately $70 per order. She has also determined that the costs of carrying the item in inventory amount to approximately $27 per unit per year (primarily direct storage costs and forgone profit on investment in inventory). Demand for the item is reasonably constant over time, and the forecast is for 16,500 units per year. When an order is placed for the item, the entire order is immediately delivered to the firm by the supplier. The firm operates 6 days a week plus a few Sundays, or approximately 320 days per year. Determine the following:
a. Optimal order quantity per order
b. Total annual inventory costs
c. Optimal number of orders to place per year
d. Number of operating days between orders, based on the optimal ordering
13-4. The Sofaworld Company purchases upholstery material from Barrett Textiles. The company uses 45,000 yards of material per year to make sofas. The cost of ordering material from the textile company is $1,500 per order. It costs Sofaworld $0.70 per yard annually to hold a yard of material in inventory. Determine the optimal number of yards of material Sofaworld should order, the minimum total inventory cost, the optimal number of orders per year, and the optimal time between orders.
13-5. The Wallace Stationary Company purchases paper from the Seaboard Paper Company. Wallace produces stationary that require 1,415,000 sq. yards of stationary per year. The cost per order for the company is $2,200; the cost of holding 1 yard of paper in inventory is $0.08 per year. Determine the following:
a. Economic order quantity
b. Minimum total annual cost
c. Optimal number of orders per year
d. Optimal time between orders
13-6. The Ambrosia Bakery makes cakes for freezing and subsequent sale. The bakery, which operates five days a week, 52 weeks a year, can produce cakes at the rate of 116 cakes per day. The bakery sets up the cake-production operation and produces until a predetermined number (Q) have been produced. When not producing cakes, the bakery uses its personnel and facilities for producing other bakery items. The setup cost for a production run of cakes is $700. The cost of holding frozen cakes in storage is $9 per cake per year. The annual demand for frozen cakes, which is constant over time, is 6000 cakes. Determine the following:
a. Optimal production run quantity (Q)
b. Total annual inventory costs
c. Optimal number of production runs per year
d. Optimal cycle time (time between run starts)
e. Run length in working days
13-7. The EastCoasters Bicycle Shop operates 364 days a year, closing only on Christmas Day. The shop pays $300 for a particular bicycle purchased from the manufacturer. The annual holding cost per bicycle is estimated to be 25% of the dollar value of inventory. The shop sells an average of 18 bikes per week. The ordering cost for each order is $250. Determine the optimal order quantity and the total minimum cost.
13-8. The Chemco Company uses a highly toxic chemical in one of its manufacturing processes. It must have the product delivered by special cargo trucks designed for safe shipment of chemicals. As such, ordering (and delivery) costs are relatively high, at $3600 per order. The chemical product is packaged in 1-gallon plastic containers. The cost of holding the chemical in storage is $50 per gallon per year. The annual demand for the chemical, which is constant over time, is 7,000 gallons per year. The lead time from time of order placement until receipt is 10 days. The company operates 310 working days per year. Compute the optimal order quantity, total minimum inventory cost, and the reorder point.
13-9. The Food Place Supermarket stocks Munchkin Cookies. Demand for Munchkins is 5000 boxes per year (365 days). It costs the store $80 per order of Munchkins, and it costs $0.50 per box per year to keep the cookies in stock. Once an order for Munchkins is placed, it takes four days to receive the order from a food distributor. Determine the following:
a. Optimal order size
b. Minimum total annual inventory cost
c. Reorder point
13-10. Kroft Foods makes cheese to supply to stores in its area. The dairy can make 350 pounds of cheese per day, and the demand at area stores is 205 pounds per day. Each time the dairy makes cheese, it costs $175 to set up the production process. The annual cost of carrying a pound of cheese in a refrigerated storage area is $12. Determine the optimal order size and the minimum total annual inventory cost.
13-11. The Shotz Brewery produces an ale, which it stores in barrels in its warehouse and supplies to its distributors on demand. The demand for ale is 1800 barrels per day. The brewery can produce 3000 barrels per day. It costs $7500 to set up a production run for ale. Once it is brewed, the ale is stored in a refrigerated warehouse at an annual cost of $60 per barrel. Determine the economic order quantity and the minimum total annual inventory cost.
13-12. The purchasing manager for the Pacific Steel Company must determine a policy for ordering coal to operate 12 converters. Each converter requires exactly 5 tons of coal per day to operate, and the firm operates 360 days per year. The purchasing manager has determined that the ordering cost is $80 per order, and the cost of holding coal is 20% of the average dollar value of inventory held. The purchasing manager has negotiated a contract to obtain the coal for $12 per ton for the coming year.
a. Determine the optimal quantity of coal to receive in each order.
b. Determine the total inventory-related costs associated with the optimal ordering policy (do not include the cost of the coal).
c. If five days' lead time is required to receive an order of coal, how much coal should be on hand when an order is placed?
13-13. The TransCanada Lumber Company and Mill processes 10,000 logs annually, operating 250 days per year. Immediately upon receiving an order, the logging company's supplier begins delivery to the lumber mill at the rate of 60 logs per day. The lumber mill has determined that the ordering cost is $1600 per order, and the cost of carrying logs in inventory before they are processed is $15 per log on an annual basis. Determine the following:
a. The optimal order size
b. The total inventory cost associated with the optimal order quantity
c. The number of operating days between orders
d. The number of operating days required to receive an order
13-14. The Goodstone Tire Company produces a brand of tire called the Rainpath. The annual demand at its distribution center is 12,400 tires per year. The transport and handling costs are $2600 each time a shipment of tires is ordered at the distribution center. The annual carrying cost is $3.75 per tire.
a. Determine the optimal order quantity and the minimum total annual cost.
b. The company is thinking about relocating its distribution center, which would reduce transport and handling costs to $1900 per order but increase carrying costs to $4.50 per tire per year. Should the company relocate based on inventory costs?
13-15. The Deer Valley Farm produces a natural organic fertilizer, which it sells mostly to gardeners and homeowners. The annual demand for fertilizer is 220,000 pounds. The farm is able to produce 305,000 pounds annually. The cost to transport the fertilizer from the plant to the farm is $620 per load. The annual carrying cost is $0.12 per pound.
a. Compute the optimal order size, the maximum inventory level, and the total minimum cost.
b. If the farm can increase production capacity to 360.000 pounds per year, will it reduce total inventory cost?
13-16. Tradewinds Imports is an importer of ceramics from overseas. It has arranged to purchase a particular type of ceramic pottery from a Korean artisan. The artisan makes the pottery in 120-unit batches and will ship only that exact amount. The transportation and handling cost of a shipment is $7600 (not including the unit cost). The importer estimates its annual demand to be 1400 units. What storage and handling cost per unit does it need to achieve in order to minimize its inventory cost?
13-17. The KVS Pharmacy is open from 10:00 a.m. to 8:00 p.m., and it receives 200 calls per day for delivery orders. It costs the pharmacy $25 to send out its cars to make deliveries. The pharmacy estimates that each minute a customer spends waiting for their order costs the pharmacy $0.20 in lost sales.
a. How frequently should KVS send out its delivery cars each day? Indicate the total daily cost of deliveries.
b. If a car could only carry six orders how often would deliveries be made and what would be the cost?
13-18. The Olde Town Microbrewery makes Townside beer, which it bottles and sells in its adjoining restaurant and by the case. It costs $1700 to set up. brew, and bottle a batch of the beer. The annual cost to store the beer in inventory is $1.25 per bottle. The annual demand for the beer is 21,000 bottles and the brewery has the capacity to produce 30,000 bottles annually.
a. Determine the optimal order quantity, total annual inventory cost, the number of production runs per year, and the maximum inventory level.
b. If the microbrewery has only enough storage space to hold a maximum of 2500 bottles of beer in inventory, how will that affect total inventory costs?
13-19. JAL Trading is a Hong Kong manufacturer of electronic components. During the course of a year it requires container cargo space on ships leaving Hong Kong bound for the United States, Mexico, South America, and Canada. The company needs 280,000 cubic feet of cargo space annually. The cost of reserving cargo space is $7000 and the cost of holding cargo space is $0.80/ft3. Determine how much storage space the company should optimally order, the total cost, and how many times per year it should place an order to reserve space.
13-20. County Hospital orders syringes from a hospital supply firm. The hospital expects to use 40,000 per year. The cost to order and have the syringes delivered is $800. The annual carrying cost is $1.90 per syringe because of security and theft. The hospital supply firm offers the following quantity discount pricing schedule.
Quantity
Price
0–999
$3.40
10,000–19,999
3.20
20,000–29,999
3.00
30,000–39,999
2.80
40,000–49,999
2.60
50,000+
2.40
Determine the order size for the hospital.
13-21. The Interstate Carpet Discount Store has annual demand of 10.000 yards of Super Shag carpet. The annual carrying cost for a yard of this carpet is $1.25, and the ordering cost is $300. The carpet manufacturer normally charges the store $8 per yard for the carpet. However, the manufacturer has offered a discount price of $6.50 per yard if the store will order 5000 yards. How much should the store order, and what will be the total annual inventory cost for that order quantity?
13-22. Kelly's Tavern buys Shamrock draft beer by the keg from a local distributor. The bar has an annual demand of 900 kegs, which it purchases at a price of $60 per keg. The annual carrying cost is $7.20, and the cost per order is $160. The distributor has offered the bar a reduced price of $52 per barrel if it will order a minimum of 300 barrels. Should the bar take the discount?
13-23. The bookstore at Tech purchases jackets emblazoned with the school name and logo from a vendor. The vendor sells the jackets to the store for $38 apiece. The cost to the bookstore for placing an order is $120, and the annual carrying cost is 25% of the cost of a jacket. The bookstore manager estimates that 1700 jackets will be sold during the year. The vendor has offered the bookstore the following volume discount schedule:
Order Size
Discount
1–299
0%
300–499
2%
500–799
4%
800+
5%
What is the bookstore's optimal order quantity, given this quantity discount information?
13-24. Determine the optimal order quantity of jackets and total annual cost in Problem 13-23 if the carrying cost is a constant $8 per jacket per year.
13-25. The office manager for the Metro Life Insurance Company orders letterhead stationery from an office products firm in boxes of 500 sheets. The company uses 6500 boxes per year. Annual carrying costs are $3 per box, and ordering costs are $28. The following discount price schedule is provided by the office supply company:
Order Quantity (boxes)
Price per Box
200–999
$16
1000–2999
14
3000–5999
13
6000+
12
Determine the optimal order quantity and the total annual inventory cost.
13-26. Determine the optimal order quantity and total annual inventory cost for boxes of stationery in Problem 13–25 if the carrying cost is 20% of the price of a box of stationery.
13-27. The 21,000-seat Air East Arena houses the local professional ice hockey, basketball, indoor soccer, and arena football teams as well as various trade shows, wrestling and boxing matches, tractor pulls, and circuses. Arena vending annually sells large quantities of soft drinks and beer in plastic cups with the name of the arena and the various team logos on them. The local container cup manufacturer that supplies the cups in boxes of 100 has offered arena management the following discount price schedule for cups:
Order Quantity (boxes)
Price per Box
2000–6999
$47
7000–11,999
43
12,000–19,999
41
20,000+
38
The annual demand for cups is 2.3 million, the annual carrying cost per box of cups is $1.90, and ordering cost is $320. Determine the optimal order quantity and total annual inventory cost.
13-28. Determine the optimal order quantity and total annual inventory cost for cups in Problem 13–27 if the carrying cost is 5% of the price of a box of cups.
13-29. The amount of denim used daily by the Southwest Apparel Company in its manufacturing process to make jeans is normally distributed with an average of 4000 yards of denim and a standard deviation of 600 yards. The lead time required to receive an order of denim from the textile mill is a constant 7 days. Determine the safety stock and reorder point if the company wants to limit the probability of a stockout and work stoppage to 5%.
13-30. In Problem 13-29, what level of service would a safety stock of 2000 yards provide?
13-31. The Paramount Paper company produces paper from wood pulp ordered from a lumber products firm. The paper company's daily demand for wood pulp is normally distributed, with a mean of 9000 pounds and a standard deviation of 1900 pounds. Lead time is eight days. Determine the reorder point if the paper company wants to limit the probability of a stockout and work stoppage to 2%.
13-32. Kelly's Tavern serves Shamrock draft beer to its customers. The daily demand for beer is normally distributed, with an average of 20 gallons and a standard deviation of 4 gallons. The lead time required to receive an order of beer from the local distributor is 12 days. Determine the safety stock and reorder point if the restaurant wants to maintain a 90% service level. What would be the increase in the safely stock if a 95% service level were desired?
13-33. The daily demand for Ironcoat paint at the Top Value Hardware Store in North Bay is normally distributed, with a mean of 30 gallons and a standard deviation of 10 gallons. The lead time for receiving an order of paint from the paint distributor is eight days. Since this is the only paint store in North Bay, the manager is interested in maintaining only a 75% service level. What reorder point should be used to meet this service level? The manager subsequently learned that a new paint store would open soon in North Bay, which has prompted her to increase the service level to 95%. What reorder point will maintain this service level?
13-34. IM Systems assembles microcomputers from generic components. It purchases its color monitors from a manufacturer in Taiwan; thus, there is a long lead time of 25 days. Daily demand is normally distributed with a mean of 3.5 monitors and a standard deviation of 1.2 monitors. Determine the safety stock and reorder point corresponding to a 90% service level.
13-35. IM Systems (Problem 13-34) is considering purchasing monitors from a U.S. manufacturer that would guarantee a lead time of eight days, instead of from the Taiwanese company. Determine the new reorder point given this lead time and identify the factors that would enter into the decision to change manufacturers.
13-36. KVS Pharmacy fills prescriptions for a popular children's antibiotic. Amoxycilin. The daily demand for Amoxycilin is normally distributed with a mean of 200 ounces and a standard deviation of 80 ounces. The vendor for the pharmaceutical firm that supplies the drug calls the drugstore's pharmacist every 30 days and checks the inventory of Amoxycilin. During a call the druggist indicated the store had 60 ounces of the antibiotic in stock. The lead time to receive an order is four days. Determine the order size that will enable the drugstore to maintain a 99% service level.
13-37. Food Place Market stocks frozen pizzas in a refrigerated display case. The average daily demand for the pizzas is normally distributed, with a mean of 8 pizzas and a standard deviation of 2.5 pizzas. A vendor for a packaged food distributor checks the market's inventory of frozen foods every 10 days; during a particular visit there were no pizzas in stock. The lead time to receive an order is three days. Determine the order size for this order period that will result in a 98% service level. During the vendor's following visit there were 5 frozen pizzas in stock. What is the order size for the next order period?
13-38. The Mediterranean Restaurant stocks a red Chilean table wine it purchases from a wine merchant in a nearby city. The daily demand for the wine at the restaurant is normally distributed, with a mean of 18 bottles and a standard deviation of 4 bottles. The wine merchant sends a representative to check the restaurant's wine cellar every 30 days, and during a recent visit there were 25 bottles in stock. The lead time to receive an order is two days. The restaurant manager has requested an order size that will enable him to limit the probability of a stockout to 5%.
13-39. The Aztec Company stocks a variety of parts and materials it uses in its manufacturing processes. Recently, as demand for its finished goods has increased, management has had difficulty managing parts inventory; they frequently run out of some crucial parts and seem to have an endless supply of others. In an effort to control inventory more effectively, they would like to classify their inventory of parts according to the ABC approach. Following is a list of selected parts and the annual usage and unit value for each:
Item Number
Annual Usage
Unit Cost
1
36
$350
2
510
30
3
50
23
4
300
45
5
18
1900
6
500
8
7
710
4
8
80
26
9
344
28
10
67
440
11
510
2
12
682
35
13
95
50
14
10
3
15
820
1
16
60
$610
17
120
20
18
270
15
19
45
50
20
19
3200
21
910
3
22
12
4750
23
30
2710
24
24
1800
25
870
105
26
244
30
27
750
15
28
45
110
29
46
160
30
165
25
Classify the inventory items according to the ABC approach using dollar value of annual demand.
13-40. The EastCoasters Bicycle Shop stocks bikes; helmets: clothing; a variety of bike parts including chains, gears, tires, wheels; and biking accessories. The shop is in a storefront location on a busy street and it has very limited storage space for inventory. It often runs out of items and is unable to serve customers. To help manage its inventory the shop would like to classify the stock using the ABC system. Following is a list of items the shop stocks and the annual demand and unit value for each:
Item Number
Annual Demand
Unit Cost
1
10
$8
2
18
16
3
36
30
4
9
1230
5
4
760
6
3
810
7
19
420
8
56
35
9
105
17
10
27
350
11
19
36
12
12
115
13
7
2300
14
10
245
15
6
665
16
18
28
17
110
$23
18
74
18
19
8
610
20
10
935
21
7
270
22
5
1400
23
5
900
24
46
67
25
32
160
26
101
45
27
83
12
28
54
16
29
14
42
30
9
705
31
7
37
32
16
26
Classify the inventory items according to the ABC approach using dollar value of annual demand.
13-41. Tara McCoy is the office administrator for the Department of Management at State University. The faculty uses a lot of printer paper and Tara is constantly reordering and frequently runs out. She orders the paper from the university central stores and several faculty have determined that the lead time to receive an order is normally distributed, with a mean of 2 days and a standard deviation of 0.5 day. The faculty have also determined that daily demand for the paper is normally distributed, with a mean of 2.6 packages and a standard deviation of 0.8 packages. What reorder point should Tara use in order not to run out 99% of the time?
13-42. The concession stand at the Shelby High School stadium sells slices of pizza during boys' and girls' soccer games. Concession stand sales are a primary source of revenue for the high school athletic programs, so the athletic director wants to sell as much food as possible; however, any pizza not sold is given away free to the players, coaches, and referees or it is thrown away. As such, the athletic director wants to determine a reorder point that will meet the demand for pizza. Pizza sales are normally distributed with a mean of 6 pizzas per hour and a standard deviation of 2.5 pizzas. The pizzas are ordered from Pizza Beth's restaurant, and the mean delivery time is 30 minutes, with a standard deviation of 8 minutes.
a. Currently the concession stand places an order when they have 1 pizza left. What level of service does this result in?
b. What should the reorder point be to have a 98% service level?
CASE PROBLEM 13.1 The Instant Paper Clip Office Supply Company
Christie Levine is the manager of the Instant Paper Clip Office Supply Company in Louisville. The company attempts to gain an advantage over its competitors by providing quality customer service, which includes prompt delivery of orders by truck or van and always being able to meet customer demand from its stock. In order to achieve this degree of customer service, it must stock a large volume of items on a daily basis at a central warehouse and at three retail stores in the city and suburbs. Christie maintains these inventory levels by borrowing cash on a daily basis from the First American Bank. She estimates that for the coming fiscal year the company's demand for cash to pay for inventory will be $17,000 per day for 305 working days. Any money she borrows during the year must be repaid with interest by the end of the year. The annual interest rate currently charged by the bank is 9%. Any time Christie takes out a loan to purchase inventory, the bank charges the company a loan origination fee of $1200 plus 2 1/4 points (2.25% of the amount borrowed).
Christie often uses EOQ analysis to determine optimal amounts of inventory to order for different office supplies. Now she is wondering if she can use the same type of analysis to determine an optimal borrowing policy. Determine the amount of the loan Christie should borrow from the bank, the total annual cost of the company's borrowing policy, and the number of loans the company should obtain during the year. Also determine the level of cash on hand at which the company should apply for a new loan given that it takes 15 days for a loan to be processed by the bank.
Suppose the bank offers Christie a discount as follows. On any loan amount equal to or greater than $500,000, the bank will lower the number of points charged on the loan origination fee from 2.25% to 2.00%. What would be the company's optimal amount borrowed?
CASE PROBLEM 13.2 The Texas Gladiators Apparel Store
The Texas Gladiators won the Super Bowl last year. As a result, sportswear such as hats, sweatshirts, sweatpants, and jackets with the Gladiator's logo are popular. The Gladiators operate an apparel store outside the football stadium. It is near a busy highway, so the store has heavy customer traffic throughout the year, not just on game days. In addition, the stadium has high school or college football and soccer games almost every week in the fall, and baseball games in the spring and summer. The most popular single item the stadium store sells is a red and silver baseball-style cap with the Gladiators' logo on it. The cap has an elastic headband inside it, which conforms to different head sizes. However, the store has had a difficult time keeping the cap in stock, especially during the time between the placement and receipt of an order. Often customers come to the store just for the hat; when it is not in stock, customers are upset, and the store management believes they tend to go to other competing stores to purchase their Gladiators' clothing. To rectify this problem, the store manager, Jessica James, would like to develop an inventory control policy that would ensure that customers would be able to purchase the cap 99% of the time they asked for it. Jessica has accumulated the following demand data for the cap for a 30-week period. (Demand includes actual sales plus a record of the times a cap has been requested but not available and an estimate of the number of times a customer wanted a cap when it was not available but did not ask for it.)
The store purchases the hats from a small manufacturing company in Jamaica. The shipments from Jamaica are erratic, with a lead time of 20 days.
In the past, Ms. James has placed an order whenever the stock got down to 150 caps. What level of service does this reorder point correspond to? What would the reorder point and safety stock need to be to achieve the desired service level? Discuss how Jessica James might determine the order size of caps and what additional, if any, information would be needed to determine the order size.
Week
Demand
1
38
2
51
3
25
4
60
5
35
6
42
7
29
8
46
9
55
10
19
11
28
12
41
13
37
14
44
15
45
16
56
17
62
18
53
19
46
20
41
21
52
22
38
23
49
24
46
25
47
26
41
27
39
28
50
29
28
30
34
CASE PROBLEM 13.3 Pharr Foods Company
Pharr Foods Company produces a variety of food products including a line of candies. One of its most popular candy items is “Far Stars,” a bag of a dozen, individually wrapped, star-shaped candies made primarily from a blend of dark and milk chocolates, macadamia nuts, and a blend of heavy cream fillings. The item is relatively expensive, so Pharr Foods only produces it for its eastern market encompassing urban areas such as New York, Atlanta, Philadelphia, and Boston. The item is not sold in grocery or discount stores but mainly in specialty shops and specialty groceries, candy stores, and department stores. Pharr Foods supplies the candy to a single food distributor which has several warehouses on the East Coast. The candy is shipped in cases with 60 bags of the candy per case. Far Stars sell well despite the fact that they are expensive at $9.85 per bag (wholesale). Pharr uses high-quality, fresh ingredients and does not store large stocks of the candy in inventory for very long periods of time.
Pharr's distributor believes that demand for the candy follows a seasonal pattern. It has collected demand data (i.e., cases sold) for Far Stars from its warehouses and the stores it supplies for the past three years, as follows.
Demand (cases)
Month
Year 1
Year 2
Year 3
January
192
212
228
February
210
223
231
March
205
216
226
April
260
252
293
May
228
235
246
June
172
220
229
July
160
209
217
August
147
231
226
September
256
263
302
October
342
370
410
November
261
260
279
December
273
277
293
The distributor must hold the candy inventory in climate-controlled warehouses and be careful in handling it. The annual carrying cost is $116 per case. The item must be shipped a long distance from the manufacturer to the distributor. In order to keep the candy as fresh as possible, trucks must be air-conditioned and shipments must be direct, and are often less-than-truckload. As a result, ordering cost is $4700.
Pharr Foods makes Far Stars from three primary ingredients it orders from different suppliers: dark and milk chocolate, macadamia nuts, and, a special heavy cream filling. Except for its unique star shape, a Far Star is almost like a chocolate truffle. Each Far Star weighs 1.2 ounces and requires 0.70 ounce of blended chocolates, 0.50 ounce of macadamia nuts, and 0.40 ounce of filling to produce (including spillage and waste). Pharr Foods orders chocolate, nuts, and filling from its suppliers by the pound. The annual ordering cost is $5700 for chocolate, and the carrying cost is $0.45 per pound. The ordering cost for macadamia nuts is $6300, and the annual carrying cost is $0.63 per pound. The ordering cost for filling is $4500, and the annual average carrying cost is $0.55 per pound.
Each of the suppliers offers the candy manufacturer a quantity-discount price schedule for the ingredients as follows:
Determine the inventory order quantity for Pharr's distributor. Compare the optimal order quantity with a seasonally adjusted forecast for demand. Does the order quantity seem adequate to meet the seasonal demand pattern for Far Stars? That is, is it likely that shortages or excessive inventories will occur? Can you identify the causes of the seasonal demand pattern for Far Stars? Determine the inventory order quantity for each of the three primary ingredients that Pharr Foods orders from its suppliers. Discuss the possible impact of the order policies of the food distributor and Pharr Foods on quality management and supply chain management.
REFERENCES
Brown, R. G. Decision Rules for Inventory Management. New York: Holt, Rinehart and Winston, 1967.
Buchan, J., and E. Koenigsberg. Scientific Inventory Management. Upper Saddle River, N.J.: Prentice Hall, 1963.
Buffa, E. S., and Jefferey Miller. Production-Inventory Systems: Planning and Control, rev. ed. Homewood, IL: Irwin, 1979.
Churchman, C. W., R. L. Ackoff, and E. L. Arnoff. Introduction to Operations Research. New York: Wiley, 1957.
Fetter, R. B., and W. C. Dalleck. Decision Models for Inventory Management. Homewood, IL: Irwin, 1961.
Greene, J. H. Production and Inventory Control. Homewood, IL: Irwin, 1974.
Hadley, G., and T. M. Whitin. Analysis of Inventory Systems. Upper Saddle River, N.J.: Prentice Hall, 1963.
McGee, J. F., and D. M. Boodman. Production Planning and Inventory Control, 2nd ed. New York: McGraw-Hill, 1967.
Starr, M. K., and D. W. Miller. Inventory Control: Theory and Practice. Upper Saddle River, N.J.: Prentice Hall, 1962.
Wagner, H. M. Statistical Management of Inventory Systems. New York: Wiley, 1962.
Whitin, T. M. The Theory of Inventory Management. Princeton, N.J.: Princeton University Press, 1957.
Chapter 13 Supplement to Operational Decision-Making Tools: Simulation
In this supplement, you will learn about...
• Monte Carlo Simulation
• Computer Simulation with Excel
• Areas of Simulation Application
Simulation is popular because it can be applied to virtually any type of problem. It can frequently be used when there is no other applicable quantitative method; sometimes it is the technique of last resort for a problem. It is a modeling approach primarily used to analyze probabilistic problems. It does not normally provide a solution; instead it provides information that is used to make a decision.
Much of the experimentation in space flight was conducted using physical simulation that re-created the conditions of space. Conditions of weightlessness were simulated using rooms rilled with water. Other examples include wind tunnels that simulate the conditions of flight and treadmills that simulate automobile tire wear in a laboratory instead of on the road.
This supplement is concerned with another type of simulation, computerized mathematical simulation. In this form of simulation, systems are replicated with mathematical models, which are analyzed with a computer. This type of simulation is very popular and has been applied to a wide variety of operational problems.
MONTE CARLO SIMULATION
Some problems are difficult to solve analytically because they consist of random variables represented by probability distributions. Thus, a large proportion of the applications of simulations are for probabilistic models.
The term Monte Carlo has become synonymous with probabilistic simulation in recent years. However, the Monte Carlo technique can be more narrowly defined as a technique for selecting numbers randomly from a probability distribution (i.e., sampling) for use in a trial (computer) run of a simulation. As such, the Monte Carlo technique is not a type of simulation model but rather a mathematical process used within a simulation.
•Simulation: a mathematical and computer modeling technique for replicating real-world problem situations.
•Monte Carlo technique: a method for selecting numbers randomly from a probability distribution for use in a simulation.
The name Monte Carlo is appropriate, since the basic principle behind the process is the same as in the operation of a gambling casino in Monaco. In Monaco devices like roulette wheels, dice, and playing cards produce numbered results at random from well-defined populations. For example, a 7 resulting from thrown dice is a random value from a population of eleven possible numbers (i.e., 2 through 12). This same process is employed, in principle, in the Monte Carlo process used in simulation models.
The Monte Carlo process of selecting random numbers according to a probability distribution will be demonstrated using the following example. The manager of ComputerWorld, a store that sells computers and related equipment, is attempting to determine how many laptops the store should order each week. A primary consideration in this decision is the average number of laptops that the store will sell each week and the average weekly revenue generated from the sale of laptops. A laptop sells for $4300. The number of laptops demanded each week is a random variable (which we will define as x) that ranges from 0 to 4. From past sales records, the manager has determined the frequency of demand for laptops for the past 100 weeks. From this frequency distribution, a probability distribution of demand can be developed, as shown in Table S13.1.
Table S13.1 Probability Distribution of Demand
Laptops Demanded per Week, x
Frequency of Demand
Probability of Demand P(x)
0
20
0.20
1
40
0.40
2
20
0.20
3
10
0.10
4
10
0.10
100
1.00
The purpose of the Monte Carlo process is to generate the random variable, demand, by “sampling” from the probability distribution, P(x). The demand per week could be randomly generated according to the probability distribution by spinning a roulette wheel that is partitioned into segments corresponding to the probabilities, as shown in Figure S13.1 on the following page.
There are 100 numbers from 0 to 99 on the outer rim of the wheel, and they have been partitioned according to the probability of each demand value. For example, 20 numbers from 0 to 19 (i.e., 20% of the total 100 numbers) correspond to a demand of zero laptops. Now we can determine the value of demand by the number the wheel stops at and the segment of the wheel.
When the manager spins this wheel, the demand for laptops will be determined by a number. For example, if the number 71 comes up on a spin, the demand is 2 laptops per week; the number 30 indicates a demand of 1. Since the manager does not know which number will come up prior to the spin and there is an equal chance of any of the 100 numbers occurring, the numbers occur at random. That is, they are random numbers .
• Random numbers: numbers that have an equal likelihood of being selected at random.
It is not generally practical to predict weekly demand for laptops by spinning a wheel. Alternatively, the process of spinning a wheel can be replicated using random numbers alone.
First, we will transfer the ranges of random numbers for each demand value from the roulette wheel to a table, as in Table S13.2. Next, instead of spinning the wheel to get a random number, we will select a random number from Table S13.3. which is referred to as a random number table. (These random numbers have been generated by computer so that they are equally likely to occur, just as if we had spun a wheel.) As an example, let us select the number 39 in Table S13.3. Looking again at Table S13.2. we can see that the random number 39 falls in the range 20–59. which corresponds to a weekly demand of 1 laptop.
By repeating this process of selecting random numbers from Table S13.3 (starting anywhere in the table and moving in any direction but not repeating the same sequence) and then determining weekly demand from the random number, we can simulate demand for a period of time. For example, Table S13.4 shows demand simulated for a period of 15 consecutive weeks.
These data can now be used to compute the estimated average weekly demand.
Figures S13.1 A Roulette Wheel of Demand
Table S13.2 Generating Demand from Numbers
The manager can then use this information to determine the number of laptops to order each week.
Although this example is convenient for illustrating how simulation works, the average demand could have been more appropriately calculated analytically using the formula for expected value. The expected value, or average, for weekly demand can be computed analytically from the probability distribution, P(x), as follows:
The analytical result of 1.5 laptops is not very close to the simulated result of 2.07 laptops. The difference (0.57 laptops) between the simulated value and the analytical value is a result of the number of periods over which the simulation was conducted. The results of any simulation study are subject to the number of times the simulation occurred (i.e., the number of trials). Thus, the more periods for which the simulation is conducted, the more accurate the result. For example, if demand were simulated for 1000 weeks, in all likelihood an average value exactly equal to the analytical value (1.5 laptops per week) would result.
Table S13.3 Random Number Table
Table S13.4 The Simulation Experiment
Week
r
Demand (x)
Revenue ($)
1
39
1
4,300
2
73
2
8,600
3
72
2
8,600
4
75
2
8,600
5
37
1
4,300
6
02
0
0
7
87
3
12,900
8
98
4
17,200
9
10
0
0
10
47
1
4,300
11
93
4
17,200
12
21
1
4,300
13
95
4
17,200
14
97
4
17,200
15
69
2
8,600
Σ = 31
$133,300
Once a simulation has been repeated enough times, it reaches an average result that remains constant, called a steady-state result . For this example, 1.5 laptops is the long-run average or steady-state result, but we have seen that the simulation would have to be repeated more than 15 times (i.e., weeks) before this result is reached.
• Steady-state result: an average result that remains constant after enough trials.
COMPUTER SIMULATION WITH EXCEL
The simulation we performed manually for this example was not too difficult. However, if we had performed the simulation for 1000 weeks, it would have taken several hours. On the other hand, this simulation could be done on the computer in several seconds. Also, our simulation example was not very complex. As simulation models get progressively more complex, it becomes virtually impossible to perform them manually, making the computer a necessity.
Although we will not develop a simulation model in computer language, we will demonstrate how a computerized simulation model is developed using Excel spreadsheets. We will do so by simulating our inventory example for ComputerWorld.
The first step in developing a simulation model is to generate random numbers. Random numbers between 0 and 1 can be generated in Excel by entering the formula, = RAND(), in a cell. Exhibit S13.1 is an Excel spreadsheet with 100 random numbers generated by entering the formula, = RAND(), in cell A3 and copying to the cells in the range A3:J12. We can copy things into a range of cells in two ways. You can first cover cells A3:J12 with the cursor; then type the formula “=RAND()” into cell A3; and finally hit the “Ctrl” and “Enter” keys simultaneously. Alternatively, you can type “=RAND()” into cell A3, “copy” this cell (using the right mouse button), then cover cells A4:J12 with the cursor, and (again with the right mouse button) paste this formula into these cells.
Exhibit S13.1
• Excel File
If you attempt to replicate this spreadsheet you will generate random numbers different from those shown in Exhibit S13.1. Every time you generate random numbers they will be different. In fact, any time you recalculate anything on your spreadsheet the random numbers will change. You can see this by hitting the F9 key and observing that all the random numbers change. However, sometimes it is useful in a simulation model to be able to use the same set (or stream) of random numbers over and over. You can freeze the random numbers you are using on your spreadsheet by first covering the cells with random numbers in them with the cursor, for example cells A3:J12 in Exhibit S13.1. Next copy these cells (using the right mouse button); then click on the “Edit” menu at the top of your spreadsheet and select “Paste Special” from this menu. Next select the “Values” option and click on “OK.” This procedure pastes a copy of the numbers in these cells over the same cells with (=RAND()) formulas in them, thus freezing the numbers in place.
Notice one more thing from Exhibit S13.1; the random numbers are all between 0 and 1, whereas the random numbers in Table S13.3 are whole numbers between 0 and 100. We used whole random numbers previously for illustrative purposes; however, computer programs like Excel generally provide random numbers between 0 and 1.
Now we are ready to duplicate our example simulation model for the ComputerWorld store using Excel. The spreadsheet in Exhibit S13.2 includes the simulation model originally developed in Table S13.4.
Exhibit S13.2
• Excel File
First note that the probability distribution for the weekly demand for laptops has been entered in cells A5:C11. Also notice that we have entered a set of cumulative probability values in column B. We generated these cumulative probabilities by first entering 0 in cell B6, then entering the formula “=A6+B6” in cell B7, and copying this formula to cells B8:B10. This cumulative probability creates a range of random numbers for each demand value. For example, any random number less than 0.20 will result in a demand value of 0, whereas any random number greater than 0.20 but less than 0.60 will result in a demand value of 1, and so on.
Random numbers are generated in cells F6:F20 by entering the formula “=RAND()” in cell F6 and copying it to the range of cells in F7:F20.
Now we need to be able to generate demand values for each of these random numbers in column F. We accomplish this by first covering the cumulative probabilities and the demand values in cells B6:C10 with the cursor. Then we give this range of cells the name “Lookup.” This can be done by typing “Lookup” directly on the formula bar in place of B6 or by clicking on the “Insert” button at the top of the spreadsheet and selecting “Name” and “Define” and men entering the name “Lookup.” This has the effect of creating a table called “Lookup” with the ranges of random numbers and associated demand values in it. Next we enter the formula “=VLOOKUP(F6,Lookup,2)” in cell G6 and copy it to the cells in the range G7:G20. This formula will compare the random numbers in column F with the cumulative probabilities in B6:B10 and generate the correct demand value from cells C6:C10.
Once the demand values have been generated in column G we can determine the weekly revenue values by entering the formula “=4300*G6” in H6 and copying it to cells H7:H20.
Average weekly demand is computed in cell C13 by using the formula “=AVERAGE(G6:G20),” and the average weekly revenue is computed by entering a similar formula in cell C14.
Notice that the average weekly demand value of 1.53 in Exhibit S13.2 is different from the simulation result (2.07) we obtained from Table S13.4. This is because we used a different stream of random numbers. As we mentioned previously, to acquire an average closer to the true steady state value the simulation needs to include more repetitions than 15 weeks. As an example, Exhibit S13.3 simulates demand for 100 weeks. The window has been “frozen” at row 16 and scrolled up to show the first 10 weeks and the last 6 on the screen in Exhibit S13.3.
DECISION MAKING WITH SIMULATION
In our previous example, the manager of the ComputerWorld store acquired some useful information about the weekly demand and revenue for laptops that would be helpful in making a decision about how many laptops would be needed each week to meet demand. However, this example did not lead directly to a decision. Next we will expand our ComputerWorld store example so that a possible decision will result.
Exhibit S13.3
• Excel File
From the simulation in Exhibit S13.3 the manager of the store knows that the average weekly demand for laptop PCs will be approximately 1.49; however, the manager cannot order 1.49 laptops each week. Since fractional laptops are not possible, either 1 or 2 must be ordered. Thus, the manager wants to repeat the earlier simulation with two possible order sizes, 1 and 2. The manager also wants to include some additional information in the model that will affect the decision.
If too few laptops are on hand to meet demand during the week, not only will there be a loss of revenue, but there will also be a shortage, or customer goodwill, cost of $500 per unit incurred because the customer will be unhappy. However, each laptop still in stock at the end of each week that has not been sold will incur an inventory or storage cost of $50. Thus, it costs the store money either to have too few or too many laptops on hand each week. Given this scenario the manager wants to order either one or two laptops, depending on which order size will result in the greatest average weekly revenue.
Exhibit S13.4 shows the Excel spreadsheet for this revised example. The simulation is for 100 weeks. The columns labeled “1,” “2,” and “4” for “Week,” “RN,” and “Demand” were constructed similarly to the model in Exhibit S13.3. The array of cells B6:C10 were given the name “Lookup.” and the formula “=VLOOKUP(F6,Lookup,2)” was entered in cell H6 and copied to cells H7:H105.
The simulation in Exhibit S13.4 is for an order size of one laptop each week. The “Inventory” column (3) keeps track of the amount of inventory available each week—the one laptop that comes in on order plus any laptops carried over from the previous week. The cumulative inventory is computed each week by entering the formula “=1+MAX(G6-H6,0)” in cell G7 and copying it to cells G8:G105. This formula adds the one laptop on order to either the amount left over from the previous week (G6–H6) or 0 if there were not enough laptops on hand to meet demand. It does not allow for negative inventory levels, called backorders. In other words, if a sale cannot be made due to a shortage, it is gone. The inventory values in column 3 are eventually multiplied by the inventory cost of $50 per unit in column 8 using the formula “=G6*50”.
If there is a shortage it is recorded in column 5 labeled “Shortage.” The shortage is computed by entering the formula “=MIN(G6-H6,0)” in cell 16 and copying it to cells 17:1105. Shortage costs are computed in column 7 by multiplying the shortage values in column 5 by $500, entering the formula “=16*500” in cell K6, and copying it to cells K7:K105.
Exhibit S13.4
• Excel File
Exhibit S13.5
• Excel File
Weekly revenues are computed in column 6 by entering the formula “=43O0*MIN(H6,G6)” in cell J6 and copying it to cells J7:J105. In other words, the revenue is determined by either the inventory level in column 3 or the demand in column 4, whichever is smaller.
Total weekly revenue is computed by summing revenue, shortage costs, and inventory costs in column 9 by entering the formula “=J6 + K6 - L6” in cell M6 and copying it to cells M7:M105.
The average weekly demand, 1.50, is shown in cell C13. The average weekly revenue, $3875, is computed in cell C14.
Next we must repeat this same simulation for an order size of two laptops each week. The spreadsheet for an order size of 2 is shown in Exhibit S13.5. Notice that the only actual difference is the use of a new formula to compute the weekly inventory level in column 3. This formula in cell G7 reflecting two laptops ordered each week is shown on the formula bar at the top of the spreadsheet.
This second simulation in Exhibit S13.5 results in average weekly demand of 1.52 laptops and average weekly total revenue of $5,107.50. This is higher than the total weekly revenue of $3,875 achieved in the first simulation run in Exhibit S13.4, even though the store would incur significantly higher inventory costs. Thus, the correct decision—based on weekly revenue—would be to order two laptops per week. However, there are probably additional aspects of this problem the manager would want to consider in the decision-making process, such as the increasingly high inventory levels as the simulation progresses. For example, there may not be enough storage space to accommodate this much inventory. Such questions as this and others can also be analyzed with simulation. In fact, that is one of the main attributes of simulation—its usefulness as a model to experiment on, called “what if?” analysis.
This example briefly demonstrates how simulation can be used to make a decision (i.e., to “optimize”). In this example we experimented with two order sizes and determined the one that resulted in the greatest revenue. The same basic modeling principles can be used to solve larger problems with hundreds of possible order sizes and a probability distribution for demand with many more values plus variable lead times (i.e., the time it takes to receive an order), the ability to backorder and other complicating factors. These factors make the simulation model larger and more complex, but such models are frequently developed and used in business.
AREAS OF SIMULATION APPLICATION
Simulation is one of the most popular of all quantitative techniques because it can be applied to operational problems that are too difficult to model and solve analytically. Some analysts feel that complex systems should be studied via simulation whether or not they can be analyzed analytically, because it provides an easy vehicle for experimenting on the system. Surveys indicate that a large majority of major corporations use simulation in such functional areas as production, planning, engineering, financial analysis, research and development, information systems, and personnel. Following are descriptions of some of the more common applications of simulation.
Simulation can be used to address many types of operational problems.
WAITING LINES/SERVICE
A major application of simulation has been in the analysis of waiting line, or queuing, systems. For complex queuing systems, it is not possible to develop analytical formulas, and simulation is often the only means of analysis. For example, for a busy supermarket with multiple waiting lines, some for express service and some for regular service, simulation may be the only form of analysis to determine how many registers and servers are needed to meet customer demand.
INVENTORY MANAGEMENT
Product demand is an essential component in determining the amount of inventory a commercial enterprise should keep. Many of the traditional mathematical formulas used to analyze inventory systems make the assumption that this demand is certain (i.e., not a random variable). In practice, however, demand is rarely known with certainty. Simulation is one of the best means for analyzing inventory systems in which demand is a random variable. Simulation has been used to experiment with innovative inventory systems such as just-in-time (JIT). Companies use simulation to see how effective and costly a JIT system would be in their own manufacturing environment without having to implement the system physically.
PRODUCTION AND MANUFACTURING SYSTEMS
Simulation is often applied to production problems, such as production scheduling, production sequencing, assembly line balancing (of in-process inventory), plant layout, and plant location analysis. Many production processes can be viewed as queuing systems that can be analyzed only by using simulation. Since machine breakdowns typically occur according to some probability distributions, maintenance problems are also frequently analyzed using simulation. In the past few years, several software packages for the personal computer have been developed to simulate all aspects of manufacturing operations.
CAPITAL INVESTMENT AND BUDGETING
Capital budgeting problems require estimates of cash flows, often resulting from many random variables. Simulation has been used to generate values of the various contributing factors to derive estimates of cash flows. Simulation has also been used to determine the inputs into rate-of-return calculations, where the inputs are random variables such as market size, selling price, growth rate, and market share.
LOGISTICS
Logistics problems typically include numerous random variables, such as distance, different modes of transport, shipping rates, and schedules. Simulation can be used to analyze different distribution channels to determine the most efficient logistics system.
SERVICE OPERATIONS
The operations of police departments, fire departments, post offices, hospitals, court systems, airports, and other public service systems have been analyzed using simulation. Typically, such operations are so complex and contain so many random variables that no technique except simulation can be employed for analysis.
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ENVIRONMENTAL AND RESOURCE ANALYSIS
Some of the more recent innovative applications of simulation have been directed at problems in the environment. Simulation models have been developed to ascertain the impact of projects such as manufacturing plants, waste-disposal facilities, and nuclear power plants. In many cases, these models include measures to analyze the financial feasibility of such projects. Other models have been developed to simulate waste and population conditions. In the area of resource analysis, numerous simulation models have been developed in recent years to simulate energy systems and the feasibility of alternative energy sources.
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SUMMARY
Simulation has become an increasingly important quantitative technique for solving problems in operations. Surveys have shown simulation to be one of the techniques most widely applied to real-world problems. Evidence of this popularity is the number of specialized simulation languages that have been developed by the computer industry and academia to deal with complex problem areas.
The popularity of simulation is due in large part to the flexibility it allows in analyzing systems, compared with more confining analytical techniques. In other words, the problem does not have to fit the model (or technique); the simulation model can be constructed to fit the problem. Simulation is popular also because it is an excellent experimental technique, enabling systems and problems to be tested within a laboratory setting.
In spite of its versatility, simulation has limitations and must be used with caution. One limitation is that simulation models are typically unstructured and must be developed for a system or problem that is also unstructured. Unlike some of the structured techniques presented in this book, the models cannot simply be applied to a specific type of problem. As a result, developing simulation models often requires a certain amount of imagination and intuitiveness that is not required by some of the more straightforward solution techniques we have presented. In addition, the validation of simulation models is an area of serious concern. It is often impossible to validate simulation results realistically or to know if they accurately reflect the system under analysis. This problem has become an area of such concern that output analysis of simulation results is a field of study in its own right. Another limiting factor in simulation is the cost in terms of money and time of model building. Because simulation models are developed for unstructured systems, they often take large amounts of staff, computer time, and money to develop and run. For many business companies, these costs can be prohibitive.
The computer programming aspects of simulation can also be quite difficult. Fortunately, generalized simulation languages have been developed to perform many of the functions of a simulation study. Each of these languages requires at least some knowledge of a scientific or business-oriented programming language.
SUMMARY OF KEY TERMS
Monte Carlo technique
a technique for selecting numbers randomly from a probability distribution for use in a simulation model.
random numbers
numbers in a table or generated by a computer, each of which has an equal likelihood of being selected at random.
simulation
an approach to operational problem solving in which a real-world problem situation is replicated within a mathematical model.
steady-state result
an average model result that approaches constancy after a sufficient passage of time or enough repetitions or trials.
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SOLVED PROBLEMS
SIMULATION
Members of the Willow Creek Emergency Rescue Squad know from past experience that they will receive between zero and six emergency calls each night, according to the following discrete probability distribution:
CALLS
PROBABILITY
0
0.05
1
0.12
2
0.15
3
0.25
4
0.22
5
0.15
6
0.06
1.00
The rescue squad classifies each emergency call into one of three categories: minor, regular, or major emergency. The probability that a particular call will be each type of emergency is as follows:
EMERGENCY TYPE
PROBABILITY
Minor
0,30
Regular
0.56
Major
0.14
1.00
The type of emergency call determines the size of the crew sent in response. A minor emergency requires a two-person crew, a regular call requires a three-person crew, and a major emergency requires a five-person crew.
Simulate the emergency calls received by the rescue squad for 10 nights, compute the average number of each type of emergency call each night, and determine the maximum number of crew members that might be needed on any given night.
SOLUTION
Step 1. Develop random number ranges for the probability distributions.
CALLS
PROBABILITY
CUMULATIVE PROBABILITY
RANDOM NUMBER RANGE, r1
0
0.05
0.05
1–5
1
0.12
0.17
6–17
2
0.15
0.32
18–32
3
0.25
0.57
33–57
4
0.22
0.79
58–79
5
0.15
0.94
80–94
6
0.06
1.00
95–99.00
1.00
EMERGENCY TYPES
PROBABILITY
CUMULATIVE PROBABILITY
RANDOM NUMBER RANGE, r2
Minor
0.30
0.30
1–30
Regular
0.56
0.86
31–86
Major
0.14
1.00
87–99.00
1.00
Step 2. Set up a tabular simulation. Use the second column of random numbers in Table S13.3.
Step S. Compute the results.
Average number of minor emergency calls per night =
Average number of regular emergency calls per night =
Average number of major emergency calls per night =
If all the calls came in at the same time, the maximum number of squad members required during any one night would be 14.
QUESTIONS
S13-1. Explain what the Monte Carlo technique is and how random numbers are used in a Monte Carlo process.
S13-2. How are steady-state results achieved in a simulation?
S13-3. What type of information for decision making does simulation typically provide?
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PROBLEMS
S13-1. The Hoylake Rescue Squad receives an emergency call every 1, 2, 3, 4, 5. or 6 hours, according to the following probability distribution:
Time Between emergency Calls (hours)
Probability
1
0.05
2
0.10
3
0.30
4
0.30
5
0.20
6
0.05
1.00
The squad is on duty 24 hours per day, 7 days per week.
a. Simulate the emergency calls for three days (note that this will require a “running,” or cumulative, hourly clock) using the random number table.
b. Compute the average time between calls and compare this value with the expected value of the time between calls from the probabilistic distribution. Why are the results different?
c. How many calls were made during the three-day period? Can you logically assume that this is an average number of calls per three-day period? If not, how could you simulate to determine such an average?
S13-2. The Dynaco Manufacturing Company produces a product in a process consisting of operations of five machines. The probability distribution of the number of machines that will break down in a week is as follows:
Machine Breakdowns per Week
Probability
1
0.10
2
0.20
3
0.25
4
0.30
5
0.05
1.00
Every time a machine breaks down at the Dynaco Manufacturing Company, either one, two, or three hours are required to fix it, according to the following probability distribution:
Repair Time (hours)
Probability
1
0.30
2
0.50
3
0.20
1.00
a. Simulate the repair time for 20 weeks and compute the average weekly repair time.
b. If the random numbers that are used to simulate breakdowns per week are also used to simulate repair time per breakdown, will the results be affected in any way? Explain.
c. If it costs $50 per hour to repair a machine when it breaks down (including lost productivity), determine the average weekly breakdown cost.
d. The Dynaco Company is considering a preventive maintenance program that would alter probabilities of machine breakdowns per week as follows:
Machine Breakdowns per Week
Probability
1
0.30
2
0.20
3
0.15
4
0.10
5
0.05
1.00
The weekly cost of the preventive maintenance program is $150. Using simulation, determine whether the company should institute the preventive maintenance program.
S13-3. The Stereo Warehouse in Georgetown sells stereo sets, which it orders from Fuji Electronics in Japan. Because of shipping and handling costs, each order must be for five stereos. Because of the time it takes to receive an order, the warehouse outlet places an order every time the present stock drops to five stereos. It costs $100 to place an order. It costs the warehouse $400 in lost sales when a customer asks for a stereo and the warehouse is out of stock. It costs $40 to keep each stereo stored in the warehouse. If a customer cannot purchase a stereo when it is requested, the customer will not wait until one comes in but will go to a competitor. The following probability distribution for demand for stereos has been determined:
Demand per Week
Probability
0
0.04
1
0.08
2
0.28
3
0.40
4
0.16
5
0.02
6
0.02
1.00
The time required to receive an order once it is placed has the following probability distribution:
Time to Receive an Order (weeks)
Probability
1
0.60
2
0.30
3
0.10
1.00
The warehouse presently has five stereos in stock. Orders are always received at the beginning of the week. Simulate the Stereo Warehouse's ordering and sales policy for 20 weeks, using the first column of random numbers in Table S13.3. Compute the average weekly cost.
S13-4. A baseball game consists of plays that can be described as follows:
Distributions for these plays for two teams, the White Sox (visitors) and the Yankees (home), are as follows:
Team: White Sox
Play
Probability
No advance
0.03
Groundout
0.39
Possible double play
0.06
Long fly
0.09
Very long fly
0.08
Walk
0.06
Infield single
0.02
Outfield single
0.10
Long single
0.03
Double
0.04
Long double
0.05
Triple
0.02
Home run
0.03
1.00
Team: Yankees
Play
Probability
No advance
0.04
Groundout
0.38
Possible double play
0.04
Long fly
0.10
Very long fly
0.06
Walk
0.07
Infield single
0.04
Outfield single
0.10
Long single
0.04
Double
0.05
Long double
0.03
Triple
0.01
Home run
0.04
1.00
Simulate a nine-inning baseball game using this information.1
S13-5. The Saki automobile dealer in the Minneapolis–St. Paul area orders the Saki sport compact, which gets 50 miles per gallon of gasoline, from the manufacturer in Japan. However, the dealer never knows for sure how many months it will take to receive an order once it is placed. It
can take one, two, or three months with the following probabilities:
Months to Receive an Order
Probability
1
.30
2
.30
3
.20
1.00
The demand per month is given by the following distribution:
Demand per Month (cars)
Probability
1
.10
2
.30
3
.40
4
.20
1.00
The dealer orders when the number of cars on the lot gets down to a certain level. In order to determine the appropriate level of cars to use as an indicator of when to order, the dealer needs to know how many cars will be demanded during the time required to receive an order. Simulate the demand for 30 orders, and compute the average number of cars demanded during the time required to receive an order. At what level of cars in stock should the dealer place an order?
S13-6. The Paymor Rental Car Agency rents cars in a small town. It wants to determine how many rental cars it should maintain. Based on market projections and historical data, the manager has determined probability distributions for the number of rentals per day and rental duration (in days only) as shown in the following tables:
Number of Customers/Day
Probability
0
.20
1
.20
2
.50
3
.10
Rental Duration (days)
Probability
1
.10
2
.30
3
.40
4
.10
5
.10
Design a simulation experiment for the car agency and simulate, using a fleet of four rental cars, for 10 days. Compute the probability that the agency will not have a car available on demand. Should the agency expand its fleet? Explain how a simulation experiment could be designed to determine the optimal fleet size for the Paymor Agency.
S13-7. The emergency room of the community hospital in Farmburg has a receptionist, one doctor, and one nurse. The emergency room opens at time zero, and patients begin to arrive sometime later. Patients arrive at the emergency room according to the following probability distribution:
Time between Arrivals (min)
Probability
5
.06
10
.10
15
.23
20
.29
25
.18
30
.14
The attention needed by a patient who comes to the emergency room is defined by the following probability distribution:
Patient Heeds to See
Probability
Doctor alone
.50
Nurse alone
.20
Both
.30
If a patient needs to see both the doctor and the nurse, he or she cannot see one before the other; that is, the patient must wait to see both together. The length of the patient's visit (in minutes) is defined by the following probability distributions:
Simulate the arrival of 20 patients to the emergency room and compute the probability that a patient must wait and the average waiting lime. Based on this one simulation, does it appear this system provides adequate patient care?
S13-8. A robbery has just been committed at the Corner Market in the downtown area of the city. The market owner was able to activate the alarm, and the robber fled on foot. Police officers arrived a few minutes later and asked the owner, “How long ago did the robber leave?” “He left only a few minutes ago,” the store owner responded. “He's probably 10 blocks away by now,” one of the officers said to the other. “Not likely,” said the store owner. “He was so stoned on drugs that I bet even if he has run 10 blocks, he's still only within a few blocks of here! He's probably just running in circles!”
Perform a simulation experiment that will test the store owner's hypothesis. Assume that at each corner of a city block there is an equal chance that the robber will go in any one of the four possible directions, north, south, east, or west. Simulate for five trials and then indicate in how many of the trials the robber is within two blocks of the store.
S13-9. Compcomm, Inc., is an international communications and information technology company that has seen the value of its common stock appreciate substantially in recent years. A stock analyst would like to predict the stock prices of Compcomm for an extended period with simulation. Based on historical data, the analyst has developed the following probability distribution for the movement of Compcomm stock prices per day:
Stock Price Movement
Probability
Increase
.45
Same
.30
Decrease
.25
The analyst has also developed the following probability distributions for the amount of the increases or decreases in the stock price per day:
Probability
Stock Price Change
Increase
Decrease
1/8
.40
.12
1/8
.17
.15
3/8
.12
.18
1/2
.10
.21
5/8
.08
.14
3/4
.07
.10
7/8
.04
.05
1
.02
.05
The price of the stock is currently 62.
Develop a Monte Carlo simulation model to track the stock price of Compcomm stock and simulate for 30 days. Indicate the new stock price at the end of the 30 days. How would this model be expanded to conduct a complete simulation of one year's stock price movement?
S13-10. The Western Outfitter Store specializes in denim jeans. The variable cost of the jeans varies according to several factors, including the cost of the jeans from the distributor, labor costs, handling, packaging, and so on. Price also is a random variable that varies according to competitors' prices. Sales volume also varies each month. The probability distributions for price, volume, and variable costs each month are as follows:
Variable Cost
Probability
$8
.17
9
.32
10
.29
11
.14
12
.08
1.00
Fixed costs are $9000 per month for the store.
Simulate 20 months of store sales and compute the probability the store will at least break even.
S13-11. Randolph College and Salem College are within 20 miles of each other, and the students at each college frequently date. The students at Randolph College are debating how good their dates are at Salem College. The Randolph students have sampled several hundred of their fellow students and asked them to rate their dates from 1 to 5 (where 1 is excellent and 5 is poor) according to physical attractiveness, intelligence, and personality. Following are the resulting probability distributions for these three traits:
Simulate 20 dates and compute an average overall rating of the Salem students.
S13-12. In Problem S13-11 discuss how you might assess the accuracy of the average rating for Salem College students based on only 20 simulated dates.
1. This problem was adapted from R. E. Trueman, “A Computer Simulation Model of Baseball: with Particular Application to Strategy Analysis,” in., R. E. Machol, S. P. Ladany, and D. G. Morrison, eds., Management Science in Sports (New York: North Holland Publishing, Co., 1976), pp. 1–14.