Melt Pool-Scale Monitoring of Laser Powder Bed Fusion

This talk gives an overview of a variety of approaches used at Carnegie Mellon to track melt pool characteristics using high speed cameras, including the analysis of high speed video frames using machine learning techniques. These include the tracking of melt pool shape as viewed from above using moderate camera speeds of 6500 fps, and its correlation to the generation of keyhole-induced flaws. Higher camera speeds near 22,000fps are used to track the emission of melt pool spatter under a variety of conditions. Ultra high speed imaging approaching 200,000 fps is being used to track variability in melt pool shape and width. Finally, color camera imaging at high speeds is being used to identify temperature fields outside of the melt pool and to some distance within it. Each of these techniques is being linked to process manipulation, modeling or other process monitoring research.