Towards Automating Model-Based Systems Engineering in Industry: An Experience Report Show others and affiliations
2024 (English) In: SysCon 2024 - 18th Annual IEEE International Systems Conference, Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2024Conference paper, Published paper (Refereed)
Abstract [en]
Designing modern Cyber-Physical Systems (CPSs) is posing new challenges to both industrial practitioners and academics. In this context, adopting cutting-edge paradigms, such as Model-Based Systems Engineering (MBSE), DevOps, and Artificial Intelligence (AI), can offer new opportunities for improving CPS design automation. While such paradigms are already jointly used in the research community to support system design activities, there is a need to fill the gap between academia and industrial practitioners. Indeed, system specification is still mainly performed manually in many industrial projects. In this paper, we present a collaboration between industrial and academic partners of the AIDOaRt European project towards a model-based approach for CPS engineering applied in one of the project use cases. We identify key challenges and corresponding solutions to enhance the automation of CPS design processes. Notably, we consider a combination of prescriptive modeling, model transformations, model views, modeling process mining, and AI-based modeling recommendations. As an initial evaluation, the proposed approach is applied to a practical industrial case study.
Place, publisher, year, edition, pages Institute of Electrical and Electronics Engineers (IEEE), 2024.
Keywords [en]
Artificial Intelligence, Cyber-Physical Systems, DevOps, Model-Based Systems Engineering, Computer aided design, Embedded systems, Industrial research, Specifications, Cutting edges, Cybe-physical systems, Design activity, Design automations, Experience report, Industrial practitioners, Model-based system engineerings, Research communities, Support systems, Cyber Physical System
National Category
Software Engineering
Identifiers URN: urn:nbn:se:mdh:diva-68049 DOI: 10.1109/SysCon61195.2024.10553610 ISI: 001259228200125 Scopus ID: 2-s2.0-85197357111 ISBN: 9798350358803 (print) OAI: oai:DiVA.org:mdh-68049 DiVA, id: diva2:1884056
Conference SysCon 2024 - 18th Annual IEEE International Systems Conference, Montreal, Canada, 15-18th April, 2024
2024-07-122024-07-122024-08-07 Bibliographically approved