| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Friction Stir Welding and Processing XIII
|
| Presentation Title |
Vibration Diagnostics Regulated Automatic Friction Stir Processing |
| Author(s) |
Shikhar Krishn Jha, Anurag Gumaste, Rajiv S Mishra |
| On-Site Speaker (Planned) |
Shikhar Krishn Jha |
| Abstract Scope |
Friction stir welding (FSW) and friction stir processing (FSP) have found their niche applications in the aerospace industry (specifically for processing lightweight aluminum alloys) to improve the strength and fatigue resistance of structures that are typically compromised at fusion-based welded joints. FSW is a solid-state joining process that plasticizes the materials by generating heat with the rotating tool. Like every other metal processing, it involves optimization of various parameters (tool design, tool insertion, tool rotation speed, tilt, traverse speed, and temperature) for a given alloy chemistry. That requires a systematic study of parametric variations. As the process is based on plasticizing the metal to flow, we have developed an in-situ characterization methodology that associates the vibration frequency and amplitude to determine the optimal process parameters on the fly by reinforced learning. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Aluminum, Sustainability, Machine Learning |