A metallurgical phase transformation framework applied to SLM additive manufacturing processes

Abstract

While significant progress has been made in the last few years, the reliability of Additively Manufactured (AM) parts is often less than desirable as they suffer from manufacturing defects and hence subpar strength and fatigue life. To address this challenge, numerical methods are sought to provide insight into the process and help accelerate progress in raising the quality of AM parts. In metal AM applications, assessing the amount of unfused powder, melt pool volumes, and metallurgical phase transformations is often of interest. In this work, we introduce a generic framework for assessing metallurgical phase transformations, building on a previously-developed general simulation framework for predicting temperature evolution, distortions, and residual stresses. Experimental work was conducted to validate numerical predictions and included temperature measurements, EBSD/XRD microstructural examinations. Additional test data from the published literature was used to validate melt pool sizes and unfused powder predictions. We conclude that the continuum-level internal state variable approach proposed here can be calibrated with a reasonable amount of effort and can be used directly to link processing conditions to microstructural features. Upcoming work investigates the influence of microstructure features on mechanical performance to address the process-structure-property-performance relationship in SLM additive manufacturing.