About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
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Additive Manufacturing: Equipment, Instrumentation and In-Situ Process Monitoring
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Presentation Title |
Automated Detection and Quantification of Spatter Generated During Laser Powder Bed Fusion Using Infrared Imaging and Computer Vision |
Author(s) |
Syed Zia Uddin, Nicholas O'Brien, Satbir Singh, Jack Beuth |
On-Site Speaker (Planned) |
Syed Zia Uddin |
Abstract Scope |
Generation of melt pool spatter is commonly seen in laser powder bed fusion (LPBF) processing. Spatter can be a source of porosity in a subsequent layer if not remelted properly. Therefore, the larger the spatter particles, the greater the threat they pose to the quality of the build. Detection and quantification of spatter, and particularly large spatter particles can be critical in LPBF quality assurance. In this research, we have developed an infrared (IR) imaging setup and associated computer vision software to identify spatter particles generated during LPBF builds. Images cover the entire build area and attention is focused on the detection of large spatter particles. Spatter counts as a function of particle size are presented. Spatter detection and quantification is successfully performed on multiple builds and spatter transport across the build area is compared to CFD simulations of argon flow and associated spatter pickup and transport. |