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Model‐based systems engineering: Motivation, current status, and research opportunities

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  • Azad M. Madni
  • Michael Sievers

Abstract

As systems continue to grow in scale and complexity, the Systems Engineering community has turned to Model‐Based Systems Engineering (MBSE) to manage complexity, maintain consistency, and assure traceability during system development. It is different from “engineering with models,” which has been a common practice in the engineering profession for decades. MBSE is a holistic, systems engineering approach centered on the evolving system model, which serves as the “sole source of truth” about the system. It comprises system specification, design, validation, and configuration management. Even though MBSE is beginning to see a fair amount of use in multiple industries, specific advances are needed on multiple fronts to realize its full benefits. This paper discusses the motivation for MBSE, and its current state of maturity. It presents systems modeling methodologies and the role of ontologies and metamodels in MBSE. It presents model‐based verification and validation (V&V) as an example of MBSE use. An illustrative example of the use of MBSE for design synthesis is presented to demonstrate an important MBSE capability. The paper concludes with a discussion of challenges to widescale adoption and offers promising research directions to fully realize the potential benefits of MBSE.

Suggested Citation

  • Azad M. Madni & Michael Sievers, 2018. "Model‐based systems engineering: Motivation, current status, and research opportunities," Systems Engineering, John Wiley & Sons, vol. 21(3), pages 172-190, May.
    • Handle: RePEc:wly:syseng:v:21:y:2018:i:3:p:172-190
    DOI: 10.1002/sys.21438
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    References listed on IDEAS

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    1. Azad M. Madni*, 2015. "Expanding Stakeholder Participation in Upfront System Engineering through Storytelling in Virtual Worlds," Systems Engineering, John Wiley & Sons, vol. 18(1), pages 16-27, January.
    2. John H. Miller, 1998. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Management Science, INFORMS, vol. 44(6), pages 820-830, June.
    3. Eppinger, Steven D. & Browning, Tyson R., 2012. "Design Structure Matrix Methods and Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262017520, December.
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    Cited by:

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    2. Gonzalo Sánchez-Barroso & Jaime González-Domínguez & Justo García-Sanz-Calcedo & Francisco Zamora-Polo, 2020. "Analysis of Learning Motivation in Industrial Engineering Teaching in University of Extremadura (Spain)," Sustainability, MDPI, vol. 12(12), pages 1-11, June.
    3. Guangying Jin, 2022. "Designer Selection for Complex Engineering System Design Projects Considering the Disciplines Demanded," Sustainability, MDPI, vol. 14(23), pages 1-25, December.
    4. L. Dale Thomas & Elizabeth Patterson, 2020. "Systems Modeling Language viewpoint utilization to facilitate shared mental models among system stakeholders," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(1), pages 128-140, January.
    5. Kathleen Giles & Kristin Giammarco, 2019. "A mission‐based architecture for swarm unmanned systems," Systems Engineering, John Wiley & Sons, vol. 22(3), pages 271-281, May.

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