Multi-scale thermal modelling and variable scan parameter optimization framework for homogeneous and predictable PBF-LB aerospace components

Abstract

In this study, a process optimization framework built around a multi-scale modelling approach to predict and prevent heat accumulation in the Laser-based Powder Bed Fusion (PBF-LB) processes is presented. A combination of low fidelity thermal Finite Element Model (FEM) and an Analytical Melt Pool Model (AMPM) is employed to optimize local scan parameters and interlayer time (ILT). The framework is validated experimentally using a WE43 magnesium alloy benchmark component, demonstrating its effectiveness in mitigating local overheating and strongly reducing porosity formation. However, combining the low fidelity FEM optimization and AMPM optimizations requires further refinement to fully leverage their strengths and improve accuracy. This research contributes to the development of more reliable and predictable PBF-LB processes for critical aerospace applications.