| About this Abstract |
| Meeting |
Additive Manufacturing Benchmarks 2022 (AM-Bench 2022)
|
| Symposium
|
Additive Manufacturing Benchmarks 2022 (AM-Bench 2022)
|
| Presentation Title |
The Additive Manufacturing Moment Measure Approach to Laser Powder Bed Fusion Process Qualification |
| Author(s) |
Samuel J.A. Hocker, Brodan Richter, Joseph N. Zalameda , Wesley A. Tayon, Erik L. Frankforter, Peter W. Spaeth , Edward Glaessgen |
| On-Site Speaker (Planned) |
Samuel J.A. Hocker |
| Abstract Scope |
Qualification of a laser powder bed fusion additive manufacturing (LPBF-AM) process requires knowledge of the multi-scale material physics during the process, per part. As the LPBF-AM build occurs, each moment is influenced by the process history. Knowledge of the build sequence can be used to generate a discretized time-space-condition point field that when coupled with a nearest neighbors’ calculation results in a generalized and fully parallel process model computation. This GPU accelerated approach was developed for part-scale analysis of build files along with in-situ process monitoring sensor data and is termed the “Additive Manufacturing Moment Measure” (AM3). The AM3 approach will be presented and then used to evaluate an AM Bench relevant geometry with synchronized in-situ process data, ex-situ nondestructive evaluation, and optical microscopy observations. These comparisons permit a better understanding of how the process actions can affect the LPBF-AM build quality and the signals generated during in-situ process monitoring. |
| Proceedings Inclusion? |
Undecided |