# Stata- The Language Of Choice For Time Series Analysis

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Consequently, that is the measure we use here. Over the group of 3673 repairable items at the base and the stock levels in place during the pre-test period from September 1, 1965 to February 28, 1966 the average fill rate was 75 percent. That was the target that was used in the optimal model for the next six-month period. Table 1-1 compares the results for the pretest and test periods. During the test period from March 1, 1966 to August 31, 1966 the measured fill rate was 76 percent, slightly higher than our target, but the required inventory investment was almost cut in half.

Simulation is of limited utility in estimating the error, because it is difficult to replicate management behavior in a computer. Furthermore, different managers will behave differently. In fact our model does include delay, because the actual man-hours spent repairing an item are usually a small fraction of the average repair time. Most of the time the item is waiting for something: parts, test equipment, maintenance personnel. What we have not modeled are the detailed queueing interactions. While it might be nice to have a more sophisticated model, we must keep in mind that the data are estimated values with substantial error - not physical constants like the speed of light which can be measured with great precision.

5 is called the inventory position in many texts. The inventory position is not a constant unless the order quantity, Q, equals one. Single-Site Inventory Model for Repairable Items 25 The stock level, s, is a constant when the order quantity is one and the reorder point is s - 1. The number of units of stock on hand, (OH), the number of units of stock due in from repair and resupply, as generalized below, (DI), and the number of backorders, (BO), are non-negative random variables. Any change in one of these random variables is accompanied by a simultaneous change in another.