| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing: Process-induced Microstructures and Defects
|
| Presentation Title |
In-situ Monitoring and Defect Detection of Direct Energy Deposition Process |
| Author(s) |
Jiahui Zhang, Xiao Shang, Yu Zou |
| On-Site Speaker (Planned) |
Jiahui Zhang |
| Abstract Scope |
Direct energy deposition (DED) enables precise control over printing parameters, facilitating the production of materials with desired microstructure. In order to ensure optimal part quality, it is crucial to employ in-situ monitoring of the melt pool and analyze its condition. In this research, we have integrated a high-speed IR camera with our customized DED machine to capture melt pool images during the printing process, varying power (P) and scan speed (v) conditions. The resulting melt tracks are then scanned using a 3D microscope to assess key features such as continuity, uniformity, and defect density. To establish a correlation between melt pool characteristics and melt track quality, a 3D convolutional neural network has been developed. Additionally, we monitor the generation of spatter and elucidate its underlying mechanism. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Machine Learning, Other |