Towards Automating Model-Based Systems Engineering in Industry - An Experience Report

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.