Apr 24, 2024
10:00am - 10:30am
Room 443, Level 4, Summit
Tao Sun1
Northwestern University1
Laser powder bed fusion (LPBF) is the most extensively used metal additive manufacturing technology due to its unique capabilities in building parts with high geometric complexity and fine features. During the LPBF process, sparks (i.e., spattered particles) can be observed following the laser scanning path, indicating the presence of high-velocity vapor arising from the melt pool. Indeed, strong metal vaporization occurs in LPBF, resulting in recoil pressure that creates a depression in the melt pool, often referred to as a keyhole. The keyhole is an important dynamic structural feature in LPBF as it influences energy coupling, metal melting mode, and defect generation. Without a keyhole, the laser is absorbed by the metal surface only once, with significant amount of energy being reflected away. In contrast, with the presence of a deep keyhole, multiple laser absorption events occur, significantly increasing laser absorption efficiency. The laser melting mode can shift from conduction to transition, stable keyhole, and then unstable keyhole as the energy input increases. When the conduction mode is applied, lack-of-fusion voids may be generated during the build. An unstable keyhole condition also leads to porosity.<br/><br/>Keyhole porosity is a major defect that hinders the widespread adoption of laser-based metal additive manufacturing technologies. With simultaneous high-speed synchrotron X-ray imaging and thermal imaging, coupled with multi-physics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with sub-millisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando X-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems.