Spatter Behavior and Melt Pool Stability Analysis for Laser Powder Bed Fusion Additive Manufacturing

Abstract During the laser powder bed fusion (LPBF) additive manufacturing (AM) process, several forces are generated due to the complex interaction between the laser and powder bed, such as vapor recoil force, surface tension force, Marangoni force, gravity, and buoyance force. These forces significantly influence the metallic spatters’ behavior and melt pool stability. The spatters and melt pool stability primarily affect the printed part dimension accuracy, surface quality, and mechanical properties. To investigate spatter behavior and melt pool stability, we recorded the LPBF process with a high-speed camera and analyzed the recorded videos using home-designed Python code. This algorithm can detect the key information about the spatter and melt pool, including the spatter amount, size, initial ejection speed and angle, melt pool size and stability. In addition, this algorithm can identify the newly generated spatters and previous existing spatters to avoid repeated spatter amount counting. We find that under the same process conditions, small spatters have relatively high initial ejection speed, while big spatters have a slow initial ejection speed. In addition, we propose a stability index to quantify the LPBF process stability based on the detected melt pool length change rate. A high stability index indicates a small number of spatters and a more stable melt pool, which can contribute to manufacturing high-quality AM parts. This new image analysis algorithm and melt pool stability index can help to analyze the recorded videos and optimize the LPBF process for printing high-quality parts with fewer spatters and high melt pool stability.