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The interval between breakdowns was simulated using Monte Carlo simulation. Then, random variables were selected and 1,000 iterations were performed. The Vlookup function in Excel was used to pick up the values from the continuous distribution. It was found that the average number of weeks to breakdown was 3.936 weeks.
Likewise, Monte Carlo simulation was used with 1,000 iterations to determine the average number of days required for the repair. Then, random numbers were used and Vlookup function was used to extract values from the discrete distribution. It was found that the average number of days requird for repair were 2.218 days.
Accordingly, a uniform distribution was used and the cost was calculated for each day. It was found that it existed between $200 and $800. The uniform distribution was then used to run a Monte Carlo simulation that used random variables and performed 1,000 iterations. The Vlookup function was used to extract values from the uniform distribution. It was found that the average cost per day was $489.2.
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These values derived from our simulation runs were used to calculate the total yearly loss for the business. Then, the average simulated values were used. It was found that the total loss per year due to downtime will be equal to $14,335.
This amount is greater than what the owners expect from the machine breakdowns. They have identified a threshold yearly loss of $12,000 or more to purchase a back-up copier. Therefore, it is clear now that they will go ahead with the purchase of the back-up copier as the yearly loss is much higher than $12,000.
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This answer is as good as the quality of the distribution data available to us. If the distributions that have been provided us are not correct, then the simulation could not be correct as well. But since the probability distributions have been calculated accurately our results are also perfect. Then, the only limitation of this study is that it relies heavily on the input data.
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