Introduction
This paper will answer the question whether or not JET Copies, a new copier company established by three friends, should purchase a smaller copier as a backup for the primary copier when the primary copier is not in service. The owners of the company have purchased a primary copier similar to the one in the dean’s school of business. During making their decision to purchase, the owners received positive information from the seller regarding the copier reliability. The price of the primary copier is $12,000. Terri, one of the owners of JET Copier, received a loan for her family to purchase the copier.
After talking to someone from the dean’s office of business, JET Copies discovered that the copier is not as reliable as they thought. To prevent loss of revenue, JET Copies uses several simulations in an attempt to estimate the loss of revenue—repair days, time between breakdowns, and number of copies per day. The price of the second copier is $8,000. If revenue lost for a year is greater than or equal to $8000, then JET should purchase. Below are my calculation after setting up and running simulations based on the information provided within the case study.
1. In Excel, use a suitable method for generating the number of days needed to repair the copier, when it is out of service, according to the discrete distribution shown.
The owners of JET Copies decided to purchase a copier similar to the one used in the college of business at State. The company they purchased the copier from touted the copier reliability. The owners of JET Copies thought they made a good decision since the copier was so reliable. After purchasing the copier, Ernie, one of the owners of JET Copies discovered from someone in the dean’s office that the copier wasn’t as reliable the company had touted. Ernie discovered the copier broke down frequently and when it did, it took between 1 and 4 days to get it repaired (Taylor, 2011). Ernie shared this information with his partners James and Terri. They decided to develop a simulation model because they were studying simulation in one of their classes. The owners knew that when the copier is not in service, revenue would be lost. Terri gathered data from the college of business and developed the below probability distribution of repair times.
Repair Time:
P(x)
Cumulative
Repair Time (Days)
0.2
0
1
0.45
0.2
2
0.25
0.65
3
0.1
0.9
4
1

(Taylor, 2011) I computed the cumulative values by using the P(x) data provided. I used 0 as my first value in B7. I then added values from =A7+B7 to get .02 in B8. I then copied my formula from B8: B10. According to the results from the cumulative values found in the chart, the probabilities numbers 0 ≥ .19 will result in a 1 day repair time, 0.2 ≥ .64 will result in a 2 day repair time, 0.65 ≥ .89 will result in a 3 day repair time, and 0.9 ≥ 1 will result in a 4 day repair time.
2. In Excel, use a suitable method for simulating the interval between successive breakdowns, according to the continuous distribution shown.
Even with regular maintenance, equipment sometimes breaks down. When this occurs, productivity and revenue are lost. The owners of JET Copies are faced with the question whether they should invest in a second copier. Before making their decision, they must determine how often the copier breaks down. No-one could provide the exact probability distribution for the time between breakdowns. But after speaking to the college of business, James estimated the time between breakdowns was probably between 0 and 6 weeks, with the probability increasing the longer the copier is not out of service (Taylor, 2011).

The probability distribution uses random variables between 0 to 6 weeks and probability is assumed to increase as time goes on. The equation is then established as f(x) = x/52 for 0