Evaluation of the Air Force Systems Command Production Rate Model and Alternate Formulations.

Abstract

The need to make decisions concerning production rate changes in today's cost conscious environment requires that accurate estimates be made of their impact on cost. The Analytic Sciences Corporation (TASC) developed a model for Air Force Systems Command (AFSC) for this purpose. This model, along with two alternative formulations of the production rate problem is the subject of this investigation. Based on this analysis it has been determined that the current AFSC model is capable of providing more accurate estimates than the standard unit learning curve model which it is derived from. The first alternative formulation, which includes an additional variable to account for changes in production rate, was shown to consistently provide more accurate estimates than the current model. Since it is based on the current formulation, it can easily be incorporated into the present AFSC model. It is recommended that Systems Command do so. The second formulation, which is based on the unit learning curve model with the exponent expressed as a function of production rate, also provides more accurate estimates than the current formulation though, not as consistently. There is evidence which suggests that this formulation is capable of providing more accurate estimates than the first alternative for certain types of programs. It is recommended that this be further investigated. (Thesis)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1985
Accession Number
ADA162260

Entities

People

  • Hugh K. Bolton

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Aerospace Industry
  • Air Force
  • Aircrafts
  • Bomber Aircraft
  • Computers
  • Cost Analysis
  • Curve Fitting
  • Data Sets
  • Department Of Defense
  • Fighter Aircraft
  • Fixed Wing Aircraft
  • Production Rate
  • Statistical Analysis
  • Statistics
  • United States
  • Weapon Systems

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Regression Analysis.