Globally interconnected markets, increasing competitive pressure and demographic changes are shaping a business world that is undergoing rapid transformation. Against this backdrop, innovation and development departments are under pressure to shorten development times whilst managing limited human and financial resources, in order to secure long-term competitiveness. At the same time, large volumes of heterogeneous and predominantly unstructured data are generated throughout the entire product development and usage process, the efficient analysis of which requires the use of new methods and procedures. 

The use of artificial intelligence (AI) is becoming increasingly important in this context. In industrial practice, a number of AI-supported applications have already become established in engineering, for example for the automated analysis of measurement and simulation data, to support quality control, or to provide knowledge-based assistance in the creation of technical documentation. These applications demonstrate that AI is capable of supporting engineering activities and making many process steps more efficient. In practice, however, it is evident that the use of AI in engineering often remains limited to isolated use cases. Integration into end-to-end research and development processes, as well as systematic linking with systems engineering methods and product development tasks, has so far only been realised to a limited extent. In particular, the transfer of successful pilot applications into routine operations, as well as their continuous evaluation and scaling across projects and product generations, represent key challenges. 

The aim of our consortium benchmarking is to identify and understand successful, tried-and-tested solutions and success factors within the consortium, and to benefit from them. Together, we want to identify the concepts, methods and approaches used by companies with successful practices, and learn how AI applications can be successfully scaled up in product development and which use cases have already proven their worth in practice.