Enginuity supports the automotive industry by automating design processes in software development. It is developing a three-layer software framework: tool, model, and AI, that enables automation, integration, and data-driven decision-making. This framework helps engineers develop efficiently, generate valuable data, and train AI to provide predictive answers to technical questions. The project delivers solutions to address rising competitive and cost pressures in the automotive sector by enabling engineers to optimize design processes. It supports environmental impact analyses and life-cycle assessments, helping industries meet regulatory requirements and customer expectations while balancing sustainability and cost efficiency.
ifak is developing generative AI methods as part of the Enginuity project to provide targeted support for model-based systems engineering (MBSE) processes in the automotive industry. The aim is to improve the quality, efficiency and traceability of design and engineering processes by automatically analysing, normalising and converting vague, ambiguous or contradictory requirements into structured data models. Building on current research into large language models and our own preliminary work in the field of requirements analysis and model-based methods, we are developing techniques for abstraction recognition, semantic linking and consistency checking, and integrating them into existing MBSE toolchains.
