Session
Swifty Session 10: The Case for Space
Location
Utah State University, Logan, UT
Abstract
In the early phases of project formulation, mission integration and test (I&T) costs are typically estimated via a wrap factor approach, analogies to similar missions adjusted for mission specifics, or a Bottom Up Estimate (BUE). The wrap factor approach estimates mission I&T costs as a percentage of payload and spacecraft hardware costs. This percentage is based on data from historical missions, with the assumption that the project being estimated shares similar characteristics with the underlying data set used to develop the wrap factor. This technique has worked well for traditional spacecraft builds since typically as hardware costs grow, I&T test costs do as well. However, with the emergence of CubeSats and nanosatellites, the cost basis of hardware is just not large enough to use the same approach. This suggests that there is a cost “floor” that covers basic I&T tasks, such as a baseline of labor and testing.
This paper begins the process of developing a parametric model for estimating Small Satellite (SmallSat) Integration & Test (I&T) costs. Parametric models are a result of a cost estimating methodology using statistical relationships between historical costs and other program variables to develop cost estimating relationships (CERs). The objective is to generate a CER equation to show a relationship between the dependent variable, cost, to one or more independent variables. We will use the results of this analysis to develop a CER that can be used to better predict SmallSat I&T costs.
Cost Considerations for Estimating SmallSat I&T
Utah State University, Logan, UT
In the early phases of project formulation, mission integration and test (I&T) costs are typically estimated via a wrap factor approach, analogies to similar missions adjusted for mission specifics, or a Bottom Up Estimate (BUE). The wrap factor approach estimates mission I&T costs as a percentage of payload and spacecraft hardware costs. This percentage is based on data from historical missions, with the assumption that the project being estimated shares similar characteristics with the underlying data set used to develop the wrap factor. This technique has worked well for traditional spacecraft builds since typically as hardware costs grow, I&T test costs do as well. However, with the emergence of CubeSats and nanosatellites, the cost basis of hardware is just not large enough to use the same approach. This suggests that there is a cost “floor” that covers basic I&T tasks, such as a baseline of labor and testing.
This paper begins the process of developing a parametric model for estimating Small Satellite (SmallSat) Integration & Test (I&T) costs. Parametric models are a result of a cost estimating methodology using statistical relationships between historical costs and other program variables to develop cost estimating relationships (CERs). The objective is to generate a CER equation to show a relationship between the dependent variable, cost, to one or more independent variables. We will use the results of this analysis to develop a CER that can be used to better predict SmallSat I&T costs.
