In integrated modeling and simulation of space exploration architectures and campaigns, the challenge is to effectively explore the breadth of the trade space while reaching sufficient depth to gain insight. The use of Design of Experiments (DOE) in this field can enable more efficient parametric studies thereby allowing more resources to be focused on detailed analysis of interesting cases. This paper presents an approach based on DOE with orthogonal arrays and presents a recent integrated modeling and trade study effort within the Constellation Program (CxP) Integrated Design Analysis Cycle (IDAC-3) as a case study~1. The DOE analysis showed that the three largest factors impacting the campaign cargo margins are spares demand uncertainty (K'-factor), lunar lander cargo capacity and consumables demand uncertainty. A related contingency analysis showed that once outpost construction is completed, from a logistics perspective the campaign can absorb failed cargo flights for up to 3 years (6 flights).
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