Mat 540 Report

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1. Days to repair As we know, the number of days in which the copier can be repaired is random. So, we will generate some random numbers between 0 and 1 and denote it by r1 then according to the given probability distribution: If 0 < r1 < 0.2, then it will take one day to repair the copier. If 0.2 < r1 < 0.65, then it will take two days to repair the copier. If 0.65 < r1 < 0.90, then it will take three days to repair the copier. If 0.90 < r1 < 1, then it will take four days to repair the copier. 2. Interval between breakdowns For this type of graphs, the continuous probability function is given by: fx=2xa2 , 0≤x≤a . Here a = 6, So: fx=2x62=2x36=x18 , 0≤x≤6 Therefore, cumulative probability function is…show more content…
So, if we take random values for r2 between 0 and 1 then we will get different values of time intervals in weeks between successive breakdowns. 3. Lost revenue It is given that they charge $0.10 per copy and number of copies sold in one day follows a uniform probability distribution between 2000 and 8000 copies. Therefore, if we chose a random variable r3 whose value is in between 2000 and 8000 then the lost revenue will be 0.1×r3×repair time. By putting different values for r3, we can get a number of lost revenues by simulation method. 4. Putting it together We will put all the random variables and calculated values together and then we have to find the cumulative number of weeks from the values for weeks which we have found in intervals between breakdowns. Now, we have to take that much values of r2 till the cumulative number of weeks reached at 52 or near about 52 such that if we will take one more value for r2 then cumulative number exceeds to 52. We are taking 52 weeks as an upper limit here because we have to find the lost revenue over the period of 1 year and 1 year contains 52…show more content…
I am somewhat confident with my answer because I used simulation process correctly to find the loss of revenue and also, I used random numbers for calculating this. There are some limitations with the simulation process. The first one is that the cumulative weeks will generally not add up to accurate 52 as in my work, the final cumulative week comes as 50.968 so this is not the revenue lost in exactly 1 year. Also, if we apply simulation again then we will get the different answer for revenue loss. Therefore, it is better to apply simulation a number of times and then take the average of all those

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