An Analysis of Air Force Economic Order Quantity Type Inventory Data with an Application to Reorder Point Calculation

摘要

One of the important uses of an Economic Order Quantity (EOQ) item's distribution of lead time demand is to set its reorder point (when to order new stock). The current Air Force system computes the reorder point by assuming that demand during lead time is normally distributed. Analysis shows that a more realistic model of observed demand patterns can be chosen from the compound Poisson family of distributions. This study uses the geometric-Poisson and constant-Poisson members of that family. Fixed and variable lead times are allowed for. The ultimate objective is to understand, as exactly as possible, the true underlying random processes involved in the EOQ supply system. A second objective is to allow for a probability model that could be implemented in a large base supply account. Data from eight federal stock groups and four bases (three CONUS and one overseas) are analyzed. Approximately 10,000 items are involved. We analyze individual customer arrival and demand processes as well as empirical lead time data. The primary emphasis is on fitting the assumed geometric-Poisson and constant-Poisson model to the data. The geometric-Poisson model is taken to be a better representation of the actual arrival and demand processes than the constant-Poisson model. Although the latter model is a cruder approximation, it represents an easier model for possible implementation. Both models are shown to be more representative of actual data than the normal distribution assumption. Both models perform better in setting hypothetical reorder points than the current model.