Greetings
To ensure the long-term success of the company and its competitiveness in a highly volatile environment, the innovation and development departments of manufacturing companies are faced with the challenges of having to develop faster with fewer resources. At the same time, complexity is increasing due to the growing integration of mechanical, electrical and software components. Additionally to this are the further requirements resulting from the sustainability transition. As product development determines not only 80% of the costs but also the environmental impact of a product over its life cycle, it is important to master these challenges and turn them into a competitive advantage. This requires new methods and tools in the innovation and development processes, which makes the use of artificial intelligence (AI) crucial.
Due to the constantly growing availability of data in the course of digitalization and rapid technological developments, there is considerable potential for the use of AI in product development. From idea generation and evaluation to product validation, AI applications can support data-based decisions, automate reocurring processes and uncover highly complex correlations, thereby increasing the efficiency of product development processes and significantly reducing time-to-market. However, the identification, integration and long-term management of AI applications pose challenges for the manufacturing industry in particular, meaning that projects often do not make it past the pilot phase. To successfully scale these solutions, domain knowledge from engineering must be combined with the methods of the technology industry.
That is why we, the Machine Tool Laboratory WZL at RWTH Aachen University and the Complexity Management Academy, are working with an industry consortium to identify successful and tried-and-tested successful practices for the AI-supported product development process.
Benefit from the benchmarking study “AI-driven Product Development” to critically examine your own approach, gain further impulses and find out about successful approaches based on the study results.
We look forward to your participation!
With best regards,
Prof. Dr. Günther Schuh
Member of the Board of Directors of Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University and the Fraunhofer Institute for Production Technology IPT