An Analysis of Models for Forecasting Repairable Carcass Returns.

Abstract

This thesis evaluates techniques for forecasting the return of failed repairable spare parts (known as carcasses) within the U. S. Navy supply system by comparing the model currently implemented i the Uniform Automated Data Processing System Inventory Control Point (UICP) program with several alternative forecasting models to determine if an improvement can be achieved in forecasting effectiveness. The current model uses an exponential smoothing procedure and applied several filtering processes to determine the appropriate smoothing constant value. The alternative models employ forecasting techniques such as moving average, moving least squares, adaptive response rate, and regression analysis. Each model is then synthesized with actual U. S. Navy supply system data and its performance measured by a set of evaluation criteria. The results indicate that the current UICP forecasting model cannot be improved substantially and that a filtering process is critical to the performance of any model applied to real world data.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1982
Accession Number
ADA124606

Entities

People

  • Douglas Martin Hartman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Data Science
  • Databases
  • Errors
  • Information Processing
  • Information Science
  • Inventory
  • Inventory Control
  • Plastic Explosives
  • Procurement
  • Regression Analysis
  • Scheduling (Production)
  • Spare Parts
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Surveys
  • Test And Evaluation

Readers

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