Quality assurance of laser welds

Purpose and goal:

This project aims to develop methods for quality assurance and optimization of laser and ultrasonically welded components. In order to reduce the production time for example new electrical machines, battery packs and also welded components in other areas, a multisensor-based system for monitoring welding quality will be developed. With the help of machine learning, the system will be monitored in real time with data collected by the system.

Digital twins of the welding processes will also be developed and combined with the latest machine learning techniques. Expected results and effects:

By using sensors in combination with digital twins for monitoring of welding quality, the project is expected to be able to use machine learning in an efficient way and contribute to reduced production times. Approach and implementation:

All project participants work together in different work packages such as "Industrial cases", "Digital twins", "Quality characterization of welds", "Sensoring for inline monitoring" and "Machine learning".