| About this Abstract |
| Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Symposium
|
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Presentation Title |
A Data Based Approach to Fault Detection and Part Qualification in Wire-arc Additive Manufacturing |
| Author(s) |
William G. Carter, Christopher Masuo, Calen Kimmell, Sudarsanam Babu, Yukinori Yamamoto, Riley Wallace, Michael Sebok, Nathan Lambert, Andrzej Nycz, Alex Walters |
| On-Site Speaker (Planned) |
William G. Carter |
| Abstract Scope |
Despite the capabilities of wire-arc additive manufacturing (WAAM) to create large scale parts with complex geometry, a lack of part specific qualification and certification has prevented its wide adoption in industry. By collecting and analyzing data during the build process, a digital twin of a part can be created and potential defects can be identified without the need for extensive destructive testing. This digital twin could lead to part specific performance predictions, increasing confidence in WAAM and leading to more widespread adoption in industry. A data acquisition and fault identification system currently in use on multiple wire-arc cells will be presented along with collected data that could be used to identify potential defects and qualify printed parts. The approach based on correlating the variations of arc voltage, current and speed on local and global changes in temperature and its effect on microstructure and properties will be discussed. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |