Simulation and Adaptive Forecasting as Applied to Inventory Control

Abstract

This paper describes a case study of selected inventory accounts maintained by a large manufacturer of rocket engines. It was hypothesized that a significant improvement in average inventory levels, number of purchase orders, and number of stockouts could be obtained by augmenting existing methods of inventory management with certain OR based techniques. These techniques included exponential smoothing of demand forecasts and statistical determination of optimum safety stock levels. Computerized simulation was used to determine: (1) the most effective parameter $(\alpha)$ values for use in the exponential smoothing formulas, (2) an estimate of the potential dollar savings obtainable if the proposed methods were implemented, and (3) a means by which these methods could be implemented. A simulation model was developed for two particular inventory accounts, its correspondence with the real world was tested, and the alpha values and anticipated dollar values were determined. Additionally, a set of curves were developed for use by inventory management to assist in determining an optimized policy for varying values of purchase order cost, inventory carrying rate, and cost of stockouts