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<p>As the Engineering Support Activity (ESA) for numerous consumable Chemical Biological items managed by the Defense Logistics Agency (DLA), Edgewood Chemical Biological Center (ECBC) must be able to complete reviews of all procurement packages within 15 calendar days. With such little lead time, it would be very beneficial if ECBC had the ability to forecast when DLA procurement actions will occur. This thesis presents an evaluation of the effectiveness of Simple Regression and Exponentially Weighted Moving Average (EWMA) forecasting models to predict the demand of Chemical Biological consumable items using the procurement history data for four specific items. Neither forecasting model proved effective at predicting the demand for the items due in large part to large variation in demand patterns. The inventory policies and supply issues which currently exist at an Army production site were investigated and it was recommended to consider Economic Order Quantity (EOQ) or Just-in-Time (JIT) inventory management models as possible alternatives to achieve smoother demand patterns. Additionally, recommendations were made to examine the integrity of the historical demand data as well as using a Multiple Regression forecast model with several causal effects in addition to time.
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<br>Subjects: Simple Regression Analysis; Exponentially Weighted Moving Average; Demand Planning; Forecasting Demand; Acquisition Lead Time; Economic Order Quantity; Just-in-Time Inventory Management</div>
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Ritchey, Chris D.</div>
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