Architecture selection trade studies in DoD acquisitions, in particular during the mandated Analysis of Alternatives (AoA) process of a Major Defense Acquisition Program (MDAP), typically select several parameters of interest and generate a comparison set of 4 or 5 potential architectures. These architectures are then individually evaluated on each parameter of interest, with the results manually compared. Measures of effectiveness (typically dealing with technical performance) and cost are independently analyzed per DoD guidance. Based on advances in model-based systems engineering (MBSE), systems architecting best practices, and analytical tools, we propose a better option to conduct a multidisciplinary optimization (MDO) for the parameters of interest, including cost, to generate the architecture that presents the best value for the government while meeting affordability and performance constraints. This allows for more potential architectures to be evaluated quickly and can lead to the identification of the most promising architectures that may not have been identified utilizing more traditional manual methods. MDO can also be demonstrated to have greater transparency, more robust uncertainty analysis, and increased flexibility in adapting to scope changes in the evaluation than a more manual approach. In this research, a satellite architecture trade study analyzing disaggregation, modular satellite development, and alternative orbits was conducted with the more manual technique per current AoA guidance, and the MDO technique utilizing the ModelCenter™ tool developed by Phoenix Integration, Inc. The results of the techniques were compared and demonstrated how MDO can capture extra value from an architecture trade study, in particular an AoA, than a more manual process. In addition, the techniques themselves were compared on the basis of cost, level of effort, uncertainty, transparency, and flexibility with the intent of identifying improved DoD guidance for MDAP acquisitions.


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    Titel :

    Model-based architecture optimization for major acquisition analysis of alternatives


    Beteiligte:
    LaSorda, Maj Michael (Autor:in) / Borky, John (Autor:in) / Sega, Ron (Autor:in)


    Erscheinungsdatum :

    2018-03-01


    Format / Umfang :

    484819 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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