Many things can go wrong when additively manufacturing (AM) metal and without in-situ process monitoring, defects can only be detected and characterized after a product is built. Most commonly, manufacturers will use a high-speed camera to keep an eye on the melt pool geometry and its variation during a short period of the laser powder bed fusion (LPBF) process.
Researchers develop deep learning alternative to monitoring laser powder bed fusion
