Analysis and Evaluation of Forecasting Methods and Tools to Predict Future Demand for Secondary Chemical-Biological Configuration Items

Abstract

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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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2013
Accession Number
ADA585604

Entities

People

  • Chris D. Ritchey

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Business Administration
  • Contracts
  • Engineering
  • Information Exchange
  • Information Science
  • Information Systems
  • Lead Time
  • Logistics
  • Management Personnel
  • Production
  • Regression Analysis
  • Statistical Analysis
  • Supply Chain
  • Supply Chain Management
  • Systems Engineering
  • Time Intervals

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Regression Analysis.