A cost model for estimating operating and support costs for US Navy (nuclear) submarines

Abstract

This thesis attempts to formulate a parametric cost model to estimate the annual operating and support (O&S) cost of future U.S. Navy (nuclear) submarines, based on presumed physical characteristics and manpower expectations. Source data for the analysis is obtained from the Navy's VAMOSC database. Using regression analysis techniques, cost estimating relationships are developed for three assumed cost drivers - manpower, length, and submerged displacement. However, the analysis reveals that there is no significant relationship between annual O&S cost and the three assumed cost drivers. Therefore, an alternative method of estimating annual O&S cost is presented using probabilistic assessment of cost based on the empirical annual O&S cost distribution. The probabilistic assessment method allows decision-makers and cost analysts to estimate the annual O&S cost for which there is a desired probability that the true annual O&S cost of a new submarine will not be exceeded. For example, historically, 80 percent of all SSNs have experienced annual O&S costs of less than $27 M (CY99$), while the remaining 20 percent have experienced annual O&S costs greater than $27 M (CY99$). So, loosely speaking, one can be approximately 80 percent confident that the annual O&S cost of a newly acquired SSN will be no more than $27 M (CY99$). Similar results can be obtained for an SSN or SSBN, and for any desired probability.