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An Integrated Cost and Performance Model to Inform Capability Selection During Early-Phase Systems Engineering: Case Analysis and Multi-Objective Optimization Open Access

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Functionality and performance have been key elements of requirements generation for major systems, especially within the Department of Defense (DoD). However, rising cost growth rates and decreasing funding has led to legislation requiring DoD to factor cost into requirements selection and to keep within cost estimates much earlier in a system's life cycle. This paper presents a mixed methodology research effort that provides three main results. First, it provides descriptive statistical analysis of current cost growth causes within DoD system. Second, it provides new cases of programs that have conducted cost and technical analysis in their early lifecycle. Third, it provides a framework that supports a combined cost and performance estimation model with greater emphasis on cost to assess the impact of specific requirements selection for major hardware/software systems. This model is used within a synthesized process derived from new cases within DoD. It also uses Multi-Objective Optimization (MOO), specifically Linear Physical Programming (LPP), as a means to better define and assess the optimal selection of capabilities in the requirements generation phase rather than the design phase. Statistical hypothesis testing shows that this framework and the use of LPP provide more optimal material solutions than SME judgment or by simply optimizing for cost. The result is a repeatable, analytical process and model that can be used throughout a system's life cycle to concurrently assess cost and technical performance.

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