AI recommendation systems: efficient design of sustainable vehicles

Comprehensive specialist knowledge from a wide range of highly complex technical disciplines is essential for the development of a vehicle. Engineers must design entire vehicles and their individual components in such a way that they are functional, safe, economical and, increasingly, sustainable. In addition to good software tools, this requires many years of experience, but a study by the “German Association of the Automotive Industry” shows that a quarter of the workforce is expected to retire within the next 10 years. In a highly competitive environment with fast development cycles, it is crucial to retain in-house knowledge and make it efficiently accessible.
 

Gaining knowledge from data: Key to efficient development processes
Fraunhofer EMI is developing an innovative AI recommendation system that generates targeted advice for efficient product design. This system extracts the specialist knowledge of experienced engineers, which is contained in the raw data and metadata of past development cycles, among other things. The knowledge gained is converted into natural language to facilitate access to this information. The system acts as a development assistant to help engineers make faster and better decisions.
 

Create a basis for decision-making: Solutions for sustainable product design
In the use case of sustainable product design, engineers have to assess the long-term effects of their design decisions on the life cycle of a product at an early stage. Relevant information on sustainability effects is often lacking, especially when data is insufficiently linked. The AI systems developed at Fraunhofer EMI offer a solution by providing a contextual embedding for the data. Engineers receive customized recommendations that help them make sustainable design decisions. This knowledge transfer increases product quality and thus the innovative strength and competitiveness of the company.