Modeling the Demand for Spare Parts: Estimating the Variance-to-Mean Ratio and other Issues

Abstract

Mathematical models are commonly used to study the performance of the Air Force's spare parts supply and repair systems. But accurate evaluations of supply policies are not possible without accurate models of the supply system, and models that understate the variability in the supply system will bias evaluations in favor of policies that rely on accurate predictions of part failures. This Note examines the model for part failures used in the Rand Corporation Supply System model, Dyna-METRIC. The ability to predict levels of parts failures is strongly affected by at least two types of uncertainty: about the numbers of failures that will occur assuming the model is correct, and about the adequacy of the model as an approximation of the process generating parts failures. The author suggests that a model that allows more variability, such as a negative binomial model, would be more appropriate for dealing with the first type of uncertainty, and the second type can be accommodated partly by using models with more parameters.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA158690

Entities

People

  • J. S. Hodges

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Binomials
  • Computational Science
  • Data Analysis
  • Estimators
  • Mathematical Models
  • Maximum Likelihood Estimation
  • Models
  • New York
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Spare Parts
  • Standards
  • United States

Readers

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