The Production Function and Airframe Cost Estimation.

Abstract

In recent years, men and governments have become keenly aware of the huge capital outlays necessary in the acquiring of new weapons systems. Increased burden on limited capital has required more complete and careful planning. This planning has led to the need for accurate and timely cost predictions of new systems. Historically, the variables affecting the future cost of aircraft airframes have been proven to be airframe weight and aircraft speed. These are often combined with learning hypothesis to form an airframe cost model. In this paper, the production function of microeconomics is combined with weight, speed, and learning to form a nonlinear cost estimation model. Nonlinear least squares regression analysis was used in evaluating this model. Although the results are inconclusive, based on the data used, weight and speed combined with learning still appear to be the best predictors of aircraft airframe cost. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1978
Accession Number
ADA065570

Entities

People

  • John A. Long

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Human Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Aerospace Industry
  • Air Force
  • Aircrafts
  • Airframes
  • Contractors
  • Corporations
  • Cost Analysis
  • Cost Models
  • Data Science
  • Databases
  • Industrial Engineering
  • Information Science
  • Military Aircraft
  • Production Rate
  • Regression Analysis
  • Statistical Analysis

Readers

  • Computational Modeling and Simulation
  • Economics
  • Structural Health Monitoring of Composite Structures.