As part of a multi-year research collaboration with SIEB & MEYER AG, Leuphana University Lüneburg is developing AI-supported assistance systems for the structured indexing of historical product and development data. The focus is on the challenge of using artificial intelligence methods (in particular large language models and semantic analysis techniques) to process accumulated and often heterogeneous technical information, such as control codes in C/C++, design drawings, circuit diagrams and technical documentation, in such a way that it can be used specifically to support product development and optimisation.

A particular goal of the project is to make reusable technical knowledge accessible and thus support the development of sustainable product generations. To this end, AI-based agents are being developed to take on recurring tasks in the development process, such as identifying functionally similar solutions in old inventories or suggesting design adjustments based on existing design principles. At the same time, a system is being developed for the automated analysis of designs with regard to ecological criteria. This combines AI-supported evaluation of design data with concepts from life cycle analysis (LCA) and life cycle inventory (LCI) in order to identify ecological optimisation potential at an early stage and to make concrete suggestions for improvement.