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World Conference on Information Systems and Technologies

WorldCIST 2021: Trends and Applications in Information Systems and Technologies pp 581–590Cite as

A Knowledge Management Approach Supporting Model-Based Systems Engineering

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1366))

Abstract

Model-based Systems Engineering (MBSE) is a noval approach to support complex system development by formalizing system artifacts and development using models. Though MBSE models provide a completely structural formalisms about system development for system developers, such large of domain specific knowledge represented by models cannot be captured as what the developers expect. This leads to a big challenge when MBSE can be widely used for complex system development. In this paper, a knowledge management approach is proposed to support an intelligent question answering scenario when implementing MBSE in system lifecycle. We make use of the GOPPRR approach to support MBSE formalisms which are transformed to knowledge graph models. Then such models provide cues for intelligent question answers through reasoning. In the case study, we make use of an auto-braking system scenario to develop MBSE models and to implement the intelligent question answering. Finally, we find the availability of our approach is evaluated which the domain engineers enable to capture their domain knowledge more efficiently.

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Notes

  1. 1.

    The details are proposed in [18].

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Acknowledgement

The work presented in this paper is supported by the EU H2020 project (869951) FACTLOG-Energy-aware Factory Analytics for Process Industries, EU H2020 project (825030) QU4LITY Digital Reality in Zero Defect Manufacturing and the InnoSwiss IMPULSE project on Digital Twins.

Author information

Authors and Affiliations

  1. Beijing Zhongke Fengchao Ltd., Beijing, China

    Pengfei Yang

  2. Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland

    Jinzhi Lu & Dimitris Kiritsis

  3. KTH-Royal Insititute of Technology, Stockholm, Sweden

    Lei Feng

  4. School of Mechnical Engineering, Beijing institute of Technology, Beijing, China

    Shouxuan Wu & Guoxin Wang

Authors
  1. Pengfei Yang
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  2. Jinzhi Lu
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  3. Lei Feng
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  4. Shouxuan Wu
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  5. Guoxin Wang
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  6. Dimitris Kiritsis
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Corresponding author

Correspondence to Jinzhi Lu .

Editor information

Editors and Affiliations

  1. ISEG, University of Lisbon, Lisbon, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. Department of Information Sciences, University of Sheffield, Lisbon, Portugal

    Ana Maria Ramalho Correia

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Yang, P., Lu, J., Feng, L., Wu, S., Wang, G., Kiritsis, D. (2021). A Knowledge Management Approach Supporting Model-Based Systems Engineering. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1366. Springer, Cham. https://doi.org/10.1007/978-3-030-72651-5_55

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