NEED – Sustainable increase in the data competence of young scientists in electromobile production

In electric vehicle production, first principle models are currently primarily used to detect rejects and quality prediction, which are created on the basis of complex tests.

Methods of machine learning can use existing plant data to learn the interdependencies of the production process. In this way, the effort for experiments can be significantly reduced.

This project primarily aims to replace the current engineering methods in the field of modeling of production processes with data-based methods and thus initiate a paradigm shift in prototyping in electromobility production.

Since the necessary competencies in the field of software design and machine learning as well as training of neural networks have not yet been sufficiently represented in the specialist community of electromobility production, an elementary task of the project is the transfer of knowledge and the exchange of competencies for the use of data-based processes.

Project duration : 09/01/2022 – 08/31/2025

Project Partner

PEM | RWTH Aachen

Helmut Schmidt University / University of the Federal Armed Forces Hamburg


Letzte Änderung: 9. November 2023