| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
2024 Undergraduate Student Poster Contest
|
| Presentation Title |
SPU-2: Anomaly Detection via In Situ Monitored Additively Manufactured Tensile Bars |
| Author(s) |
Annika E. Bauman, Dan Bolintineanu, Anthony Garland, Michael Heiden |
| On-Site Speaker (Planned) |
Annika E. Bauman |
| Abstract Scope |
In situ monitoring of Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) leverages various sensors, including optical, and thermal, to detect anomalous process behaviors. Oak Ridge National Laboratory has developed the software Peregrine to assist users in identifying such anomalies based on optical in situ data. Peregrine was applied to in situ data from a full build plate of tensile bars, produced under varying process parameters, to detect anomalies. These tensile bars subsequently underwent tensile testing, revealing property variations within each process parameter set. This presentation will showcase the use of a variety of sensors to capture defects and process signatures in a tensile build. The discussion will cover tensile testing results, correlating them with Peregrine-identified anomalies and ground truth computed tomography (CT) scans, to elucidate the impact of process parameters on anomaly behaviors. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525 |