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Enhancing Knowledge Management into Systems Engineering through New Models in SysML

Author

Listed:
  • Julien Gardan

    (EPF - Ecole Polytechnique Féminine-Sceaux 92330)

  • Nada Matta

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper aims at exploring cooperative work and knowledge implication into Systems Engineering approach in order to study organisational impact. Furthermore, the study aims at providing conceptual models that enhance a Model-Based Systems Engineering (MBSE) with the purpose of taking into account knowledge management (KM). The research formulates a decision model that complements the existing methods through Systems Modeling Language (SysML). The methodology is based on current SysML diagrams and proposes a KM solution focused on an organizational approach. The requirements satisfaction is built on this conceptual approach to help on the decisional process. Systems Engineering (SE) integrates all the disciplines and specialty groups into a team effort forming a structured development process from design to production. SE shows that cooperative work and management increase with the complexity of systems. Thus far, the current models do not present enough cooperative and knowledge management supports. The study proposes to add a new model to imply KM and organizational aspect through SysML in order to develop a cooperative work process with a first conceptual approach. This paper tackles several possibilities based on modeling language SysML extension and discusses the interest of implementing the model while providing a complementary decision-making tool.

Suggested Citation

  • Julien Gardan & Nada Matta, 2017. "Enhancing Knowledge Management into Systems Engineering through New Models in SysML," Post-Print hal-02893990, HAL.
  • Handle: RePEc:hal:journl:hal-02893990
    DOI: 10.1016/j.procir.2017.01.052
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    Cited by:

    1. Li, Rui & Verhagen, Wim J.C. & Curran, Richard, 2020. "A systematic methodology for Prognostic and Health Management system architecture definition," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

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