Multiscale numerical feedforward optimization of the Laser Powder Bed Fusion process

Laser Powder Bed Fusion is an additive manufacturing technique used to produce solid metal parts from metallic powder. It excels at producing complex geometries in small batches. However, processing conditions are still being optimized using time and labor intensive trial and error approaches. Even after optimization, the contrast between the complex geometry and the limited set of optimized processing conditions, yields a compromise between printability and melt pool homogeneity at best. We propose a multiscale modeling approach to obtain a physics driven prediction of processing conditions tailored to a specific geometry. The workflow consists of two distinct modeling techniques utilized to capture the physics of the process both, on the part scale, and on the melt pool scale. The optimization strategy, which couples the two modelling approaches, aims to minimize melt pool variations in the vicinity of geometric features. In-situ high speed thermal imaging unveils the effectiveness of the approach and illustrates a reduction of 89% of systematic melt pool variations throughout the print of a complex geometry. Moreover, stochastic melt pool variations could be quantified. As a whole, this approach allows for the drastic reduction in systematic melt pool variations in complex parts, and will resultingly allow the fine tuning of microstructures in the presence of varying thermal boundary conditions.