MATH540 Week 3 Assignment, Chapter 14, Jet Copies, Set up

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MATH540 Week 3 Assignment, Chapter 14, Jet Copies, Set up

Provided by Professor Aungst, Supplemental Instruction

Information from Jet Copies Case Study:

- Students bought an $18,000 copier to start their own copy business.

- Wanted to purchase a smaller copier for $8,000 as back-up

- Created a simulation to estimate the amount of revenue that would be lost if they did not have a backup

- Time between breakdowns is 0 weeks to 6 weeks (see probability function on page 679, and provided later in this set up

- Developed following probability distribution of repair times:

Repair Time (days)

Probability

1

0.20

2

0.45

3

0.25

4

0.10

 

- Estimated they would sell between 2,000 and 8,000 copies per day at 10 cents (0.10) per copy

- Used a uniform probability distribution between 2,000 and 8,000 to estimate how many copies they would sell per day

- If loss of revenue due to machine downtime during 1 year is greater than or equal to $12,000, then they should purchase the back-up copier

- Decided to conduct a manual simulation of this process for 1 year to see if the model was working correctly

- Our assignment is to perform this manual simulation for JET copies and determine the loss of revenue for 1 year.

Here’s some preliminary Set Up information:

The probability function for time between repairs, f(x), is,

 

f(x) = x/18,  0 <= x <= 6

 

and,  r = x^2/36

 

x2 = 36r

 

x = 6*sqrt of r (use this formula in the column you designate as time between repairs)

 

 

You could develop the cumulative distribution and random number ranges for the distribution of repair times for reference if you would like that for reference.

 

Repair Time

Repair Time

Cumulative Probability

RN Ranges

y (days)

P(y)

 

 

1

0.2

 

 

2

0.45

 

 

3

0.25

 

 

4

0.10

 

 

 

The probability function for daily demand is developed by determining the linear function

for the uniform distribution, which is,

 

f(z) = 1 / b – a which equals 1/6

 

Letting F(z) = r in the Integrated Function, and solving for z we get:  z = 6r + 2 (this is the formula for copies lost)

 

There are various ways to set up the Monte Carlo simulation in Excel using the formulas we learned in Chapter 14 … namely Random Number Generation (which is =RAND) and VLOOKUP which allows us to “point back” to a probability table and insert a probability based on that Random Number and the Probability associated with it in the table.

 

Most students start with developing the probability table for Repair time to later be used as the VLOOKUP Table for Repair Time probability. 

 

P(x)

Cumulative

Repair Time

   
   
   
   
   

 

 

The Simulation itself would be for 52 weeks (which would be when the cumulative “time between breakdowns” reached 52 weeks).  You could begin with a Random Number (r1) which would be multiplied by column 2, the Time Between Breakdown (in weeks) formula of 6*square root of r1

 

You could then sum those variables in a cumulative list in column 3 (so you could tell when the simulation reached 52 weeks). 

 

In column 4 you could generate another random number (say, r2) to calculate the column 5 Repair time in y days. 

 

That r2 could be used in a column 5 for Repair Time in y days which could be calculated by using the =VLOOKUP function which would relate that r2 to probabilities in the Repair Time probability table originally set up.

 

You might then set up some random number columns and result columns for repairs taking 1 day, 2 days, 3 days and 4 days.

 

At some point, you would need to figure out how to calculate copies lost in a day in thousands and that would probably include the formula z = 6r + 2

 

Finally, you would want to equate the number of copies lost to the revenue lost at 10 cents per copy and then cumulate that for all 52 weeks to find the annual lost revenue.

 

 

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