Machine Learning Enhanced Process Simulation in Laser Powder Bed Fusion (LPBF)
At a glance
- Project leader : Dr. Thomas Mayer
- Deputy of project leader : Prof. Dr. Robert Eberlein
- Project team : Bianca Egli, Matthias Huber, Ibrahim Kuon, Maurus Sonderegger
- Project budget : CHF 690'307
- Project status : ongoing
- Funding partner : Innosuisse (Innovationsprojekt / Projekt Nr. 50397.1 IP-ENG)
- Project partner : ABB Schweiz AG, Sauber Engineering AG
- Contact person : Thomas Mayer
Description
The project aims to develop and implement dedicated calibration procedures and parts that are tailored to critical applications of ABB and Sauber, to improve the accuracy of distortion predictions for specific components. Machine learning is then used to enhance simulations also beyond the calibrated regime. This accuracy and flexibility are essential for the successful compensation of arbitrary geometries in industry.Process simulation-based distortion compensation will be implemented to improve the productivity and profitability of Laser Powder Bed Fusion (LPBF) and to reduce lead times. Dedicated calibration procedures will be developed and enhanced by Machine Learning methods for generalized applicability.