A First Step Towards AI for MBSE: Generating A Part of SysML Models From Text Using AI


Model-Based Systems Engineering (MBSE) and Artificial Intelligence (AI) have been challenged concerning their successful deployment in real-world applications. In this paper, we aim to contribute with a first step towards applying AI for MBSE to optimize the MBSE adoption and resolve a set of its challenges. Particularly, we present the text-to-model part of the SysDICE framework dealing with the generation of SysML models from semi-structured input text using natural language processing and machine learning techniques. Namely, the text-to-model framework and method activities are described and demonstrated with an example from the rail sector. With this contribution, we aim first to argue about the potential of AI to help in enhancing the MBSE adoption and second to trigger the AI and MBSE communities for further discussions and industrial applications.


Mohammad Chami – Chami Consulting
Christophe Zoghbi – ZAKA SAL
Jean-Michel Bruel – University of Toulouse

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