The Production Function and Airframe Cost Estimation.
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING
Pagination or Media Count:
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
- Economics and Cost Analysis