Probabilistic simulation of multi-stage decisions for operation of a fractionated satellite mission

We present two complementary analysis models to study the effect of programmatic management decisions on the distribution of net present value for a fractionated satellite constellation. The goal is to begin development of an approach to quantify when system attributes associated with design flexibility have realizable benefits for space systems. The first approach is a heuristics-based decision model, which utilizes a Monte Carlo simulation to produce value distributions for satellite operator decision sets; the second approach is a multi-stage decision process model, which utilizes a dynamic programming algorithm to find value-optimal decisions. We use a generic Department of Defense (DoD) terrestrial weather satellite program as a case study for analysis. We find evidence that technological evolution of a fractionated satellite system within the scope of a single program may not be desirable due to cost and schedule risks.