AI-MBSE-Assisted Requirements Writing and Management – Towards a Knowledge-Based Framework
DS 134: Proceedings of the 26th International DSM Conference (DSM 2024), Stuttgart, Germany
Year: 2024
Editor: Harold (Mike) Stowe; Christopher Langner; Matthias Kreimeyer; Tyson R. Browning; Steven D. Eppinger; Ali A. Yassine
Author: Ali Asghar Bataleblu; Erik Felix Tinsel; Benjamin Schneider; Erwin Rauch; Armin Lechler; Oliver Riedel
Series: DSM
Institution: Faculty of Engineering, Free University of Bozen-Bolzano; Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW), University of Stuttgart; Fraunhofer Institute for Industrial Engineering IAO, Stuttgart
Page(s): 050-058
DOI number: 10.35199/dsm2024.06
Abstract
In transitioning to digital twins (DTs), the variety in requirements and their interactions impedes the effectiveness and efficiency of the developed DTs. The experts' information exchange and multi-domain dependency extraction are crucial in creating a practical DT. Interpreting a physical system's requirements through a knowledge-based approach into a new set of requirements in the digital domain, and connecting and tracing them concurrently, can significantly narrow the gap between digital twins and practical needs. This paper proposes an artificial Intelligence (AI) assisted tech-driven requirements writing and management framework based on the axiomatic design (AD) theory and a model-based systems engineering (MBSE) cloud. An outline of the envisioned framework is sketched on a W-model, one V is physical system and the other corresponds to digital model. The intersection of both V is where the interface will be managed to close the gap. Finally, the challenges in developing such a framework are discussed.
Keywords: Requirements Management, Digital Twins, Model-based Systems Engineering, Artificial Intelligence, Axiomatic Design