| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advanced Real Time Imaging
|
| Presentation Title |
Mapping the Melt Pool Variability in L-PBF Additive Manufacturing by High-Speed Imaging |
| Author(s) |
David Guirguis, Conrad Tucker, Jack Beuth |
| On-Site Speaker (Planned) |
David Guirguis |
| Abstract Scope |
Laser powder bed fusion (L-PBF) is a well-established technology for additive manufacturing of metal alloys. However, the uncertainty and variability in the quality of printed parts are still of major concern. Insights into the variability of melt pool dimensions are crucial to determine process parameters for microstructural control and enhancement of mechanical properties. Additionally, significant variability can lead to flaws. In this work, we analyze and quantify the variation in melt pool attributes by utilization of high-speed imaging at a frame rate of up to 216,000 frames per second. Quantification and mapping of the melt pool variation are performed with different process parameters for Ti-6Al-4V and ultra-high-strength steel alloy AF–9628. The results of this study can help better understand the correlation between the dimensional variability and the process parameters. In addition, computational models for optimum hatch spacing are developed employing Bayesian machine learning. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Characterization, Machine Learning |