Design-a-simulation-to-help-Jane-determine-how-many-order-pickers-she-should-hire

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Part I (15 points):

A warehouse manager, Jane, needs to determine how many order pickers she should staff. The daily demand is normally distributed with a mean of 58,855 orders and a standard deviation of 4876 orders. The number of orders that order pickers pick daily is normally distributed with a mean of 6012 orders and a standard deviation of 163 orders.

Design a simulation to help Jane determine how many order pickers she should hire so that demand is satisfied at least 97.5% of the time.

Part II (10 points):

Jane has instructed her QA Department to inspect the picked orders for order accuracy because sales has been reporting that many customers have complaints about inaccurate orders. QA reports that the yield is normally distributed with a mean of 98.8% and a standard deviation of 0.43% which Jane finds unsatisfactory. She has mandated a minimum yield of 99%! The QA Department and Operations have started to design a Six Sigma improvement project to increase the yield to at least 99% but this will take months to complete.

In the meantime, Jane has ordered QA to hire scanners who will inspect the orders and repair the inaccurate orders. QA reports that this has been done in the past and the scanners achieve a 100% yield on the scanned orders. Their output is normally distributed with a mean of 2133 orders and a standard deviation of 97 orders.

Design a simulation to help Jane determine how many order scanners she should hire to achieve the 99% minimum yield.

Note 1: Yields cannot exceed 100%

Note 2: The final yield is calculated as:

[((Original demand – Orders scanned) * Yield) + Orders Scanned]/Original demand

 
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