In-process Multi-physics Melt Pool Measurement and Correlation Analysis in Laser Powder Bed Fusion

Abstract Laser powder bed fusion still suffers from defects such as delamination and porosities due to the lack of understanding of melt pool dynamics. To study the fundamental of the melt pool behavior, both geometrical and thermal sensing with high spatial and temporal resolutions are necessary. This work applies and integrates three advanced sensing technologies: synchrotron X-ray imaging, high-speed IR camera, and high-spatial-resolution IR camera to characterize the melt pool dynamics, keyhole, porosity formation, vapor plume, and thermal evolution in Ti-64 and 410 stainless steel. This paper develops an effective algorithm for high-speed X-ray imaging data to identify melt pool geometries accurately. Pre-processing methods are also implemented for the IR data to estimate the emissivity value and extrapolate the saturated pixels. Quantifications on boundary velocities, melt pool dimensions, thermal gradient, and cooling rates are performed, which provides a thorough understanding of the melt pool with integrated geometrical and thermal perspectives. The study discovers a strong correlation between the thermal and X-ray data, enabling the feasibility of using relatively cheap IR cameras to predict features that currently can only be captured using the costly synchrotron X-ray imaging. Such correlation enables the thermal-based melt pool control as well.