Parametric cost estimation for space science missions

Abstract

Cost estimation for space science missions is critically important in budgeting for successful missions. The process requires consideration of a number of parameters, where many of the values are only known to a limited accuracy. The results of cost estimation are not perfect, but must be calculated and compared with the estimates that the government uses for budgeting purposes. Uncertainties in the input parameters result from evolving requirements for missions that are typically the "first of a kind" with "state-of-the-art" instruments and new spacecraft and payload technologies that make it difficult to base estimates on the cost histories of previous missions. Even the cost of heritage avionics is uncertain due to parts obsolescence and the resulting redesign work. Through experience and use of industry best practices developed in participation with the Aerospace Industries Association (AIA), Northrop Grumman has developed a parametric modeling approach that can provide a reasonably accurate cost range and most probable cost for future space missions. During the initial mission phases, the approach uses mass- and powerbased cost estimating relationships (CER)'s developed with historical data from previous missions. In later mission phases, when the mission requirements are better defined, these estimates are updated with vendor's bids and "bottoms- up", "grass-roots" material and labor cost estimates based on detailed schedules and assigned tasks. In this paper we describe how we develop our CER's for parametric cost estimation and how they can be applied to estimate the costs for future space science missions like those presented to the Astronomy & Astrophysics Decadal Survey Study Committees.