An Application of Linear Regression to the Allocation of General Purpose Vehicles

Abstract

The purpose of this thesis was to develop a mathematical model which could assist in the allocation of general purpose vehicles. The linear regression model developed was used, through the AFIT CSC computer system, within the SAS statistical software program. Data was obtained from two AFSC bases. Their input, through the SAS interaction, led to the following model: Y (predicted maintenance cost) = beat sub 0 + beta sub 1 X sub 1 + beat sub 2 x sub 2 where X sub 1 equals age and X sub 2 equals average miles driven. The analysis demonstrated the statistical significance of the model. It also highlighted the potential for its application to include all bases within a command. The data limitation, only two bases in the sample, restricted the analysis from making any macro statements; however, it appears from the minor differences in regression coefficients, as well as similar mean fleet ages and mean miles traveled, the current distribution system is an effective one. This is to say that the current system of allocation used by the AFSC/LGT, the fair share method is effective at keeping maintenance costs, as well as vehicle assets, balanced across the AFSC fleet.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1986
Accession Number
ADA174566

Entities

People

  • John H. Golden

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Bayesian Networks
  • Business Administration
  • Computational Science
  • Databases
  • Literature Surveys
  • Maintenance
  • Maintenance Costs
  • Maintenance Management
  • Mathematical Models
  • Models
  • Probability
  • Probability Distributions
  • Procurement
  • Regression Analysis
  • Security

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computer Science.
  • Life Cycle Cost Analysis