Project title: Melting-Process-Condition Variations-Aware Control of the Laser-Powder Bed Fusion of Metals
Acronym: MeltingWell
Type of project: EU projects
Role: Principal Investigator
Financing: Horizon Europe
Duration: 01.01.2026 – 31.12.2030
Laboratory: Laboratory for Mechatronics, Production Systems and Automation LAMPA
Project description:
Laser-powder bed fusion of metals (PBF-LB/M), also known as selective laser melting (SLM), enables the production of geometrically complex and high-performance metal parts, such as medical implants, nature-inspired structures, and aircraft structural elements. In PBF-LB/M, the laser beam melts metal powder layer after layer, resulting in a solidified metal bulk piece and/or lattice structure. PBF-LB/M supports sustainability through light-weighting, easing supply chain constraints, and enables a high level of product customization. However, the PBF-LB/M process is limited by process condition variations, which often cause defects and quality variations in the printed parts. For example, due to the heat accumulation effect and specific laser toolpath pattern, the depth of melting will vary despite using constant process input parameters such as laser power and scan speed. The inability to predict and control melting process condition variations leads to qualification and certification challenges, hence hindering the wide adoption of this process in industry. The discovery of feasible and effective control methods that can reduce melting process condition variations is critical for the adoption and further advancement of the PBF-LB/M process.
The goal of this project is to develop and validate the first solution for controlling the PBF-LB/M process, which takes into account all common sources of process condition variations. The control solution will be based on the PI’s recent breakthrough results in predicting process condition variations in PBF-LB/M. The proposed solution is in i) improved coaxial measuring of meltpool depth variations, ii) combining two state-of-the-art data-driven process condition prediction models, and iii) generating predetermined dynamic adjustments of the laser power along the scan path. The proposed control method’s validation will determine the next de facto standard control method for PBF-LB/M.