A parametric cost model for estimating acquisition costs of conventional U.S. Navy Surface Ships

Abstract

When attempting to predict the acquisition costs of U.S. Navy surface ships, current models cannot produce a repeatable answer when the details of the acquisition program are not well defined. This thesis formulates a parametric model that predicts the average procurement cost of a conventional U.S. Navy surface ship based upon known (or assumed) physical and performance characteristics. The source data for the cost model is obtained from U.S. Weapons Systems Costs, a tabulation of annual procurement costs for major system programs, published by Data Search Associates. Standard regression techniques return cost estimating relationships able to predict average procurement cost from ship light displacement, ship overall length, ship propulsion shaft horsepower or number of propulsion engines. The formulated parametric cost model is approximate and appropriate only for rough order of magnitude studies, but can be used by the DoD cost community to produce justifiable estimates when other models do not have sufficient information to generate an answer.