Advanced Digital Integration: from Legacy Data to Model-Based Systems Engineering

The challenge of effectively converting information from legacy products into model-based representations is a significant barrier to the adoption of Model-Based Systems Engineering (MBSE) in the industry. Among many aspects, MBSE is a paramount discipline for the Digital Integration demanded by companies. To solve this challenge, a new Method has been proposed that transforms unstructured and difficult-to-analyze information into a structured and easily understandable form, laying the foundation for cooperation between this information and digital systems. This leads to an improvement in company efficiency, allowing them to employ innovative digital tools alongside legacy ones. It improves the traceability of requirements, bolsters the evaluation of system performance, and mitigates errors through rigorous model simulations and analyses. By maintaining consistent information throughout all stages of the system’s lifecycle, MBSE significantly reduces the time and costs associated with development. A chapter dedicated to how Model-Based Systems Engineering has strong mathematical foundations clarifies the reliability of this discipline for both current and future use. Finally, this Method, with the advent of Artificial Intelligence (AI), will enable rapid integration between Model-Based Systems Engineering and AI, allowing for new developments to keep pace with emerging challenges.