Framework for circular AI-driven model-based systems engineering

The development of interdisciplinary Smart Products involves complex architectures and processes, which results in new challenges like managing heterogeneous and unstructured data causing inefficiencies. Model-Based Systems Engineering (MBSE) addresses these issues through precise system modeling but encounters obstacles like a lack of model reuse and complexity. This paper introduces a novel framework integrating Artificial Intelligence into MBSE to enhance sustainability and circularity by automating model generation and reusing existing system models. Using ontology-based knowledge management and large language models, model creation, interoperability, and decision-making can be enhanced and automated and visualized in real-time. The framework's capabilities and benefits are demonstrated through the instantiation of a wireless charger system example.