A probability distribution for the number of machines

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A factory manager must decide whether to stock a particular spare part. The part is ab solutely essential to the operation of certain machines in the plant. Stocking the part costs $10 per day in storage and cost of capital. If the part is in stock, a broken machine can be repaired immediately, but if the part is not in stock, it takes one day to get the part from the distributor, during which time the broken machine sits idle. The cost of idling one machine for a day is $65. There are 50 machines in the plant that require this particular part. The probability that any one of them will break and require the part to be replaced on any one day is only 0.004 (regardless of how long since the part was previously re placed). The machines break down independently of one another.

If you wanted to use a probability distribution for the number of machines that break down on a given day, would you use the binomial or Poisson distribution? Why?

Whichever theoretical distribution you chose in part a, what are appropriate parame- ters? That is, if you chose the binomial, what are the values for and nl If you chose the Poisson, what is the value for m?

c If the plant manager wants to minimize his expected cost, should he keep zero, one, or two parts in stock? Draw a decision tree and solve the manager's problem. (Do not forget that more than one machine can fail in one day!)

Reference no: EM131134546

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