Machine Learning Enhanced Process Simulation in Laser Powder Bed Fusion (LPBF) (LPBF)
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.
Key Data
Projectlead
Deputy Projectlead
Project team
Bianca Egli, Matthias Huber, Ibrahim Kuon, Maurus Sonderegger
Project partners
ABB Schweiz AG; Sauber Engineering AG
Project status
completed, 08/2021 - 07/2024
Funding partner
Innovationsprojekt / Projekt Nr. 50397.1 IP-ENG
Project budget
690'307 CHF