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

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