About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advanced Real Time Imaging for Materials Science and Processing
|
| Presentation Title |
Real-Time Thermal Feedback for Deterministic Microstructure Engineering in Laser Powder Bed Fusion |
| Author(s) |
Ankita Roy, Rajiv Mishra, Yash Parikh |
| On-Site Speaker (Planned) |
Yash Parikh |
| Abstract Scope |
Part qualification in Laser Powder Bed fusion (LPBF) is hindered by spatial and temporal variations in thermal profiles during fabrication, leading to microstructural variations, such as grain size, phase distribution, lath width, and precipitate morphology, which impacts mechanical reliability and performance. We introduce a closed-loop control (CLC) strategy that combines high-fidelity in-situ thermal monitoring with real-time laser-power modulation to precisely manage these microstructural attributes. Our approach integrates optical tomography (OT) and melt pool monitoring (MPM) guided signals with real-time laser power modulation. Advanced machine learning (ML) algorithms are employed to process in-situ signals, detecting deviations from desired thermal baseline and dynamically adjusting laser-power. We demonstrate a correlation between actively controlled thermal histories and resulting microstructural evolution across complex geometries. Comparing builds with and without CLC, we establish an ML-based framework to accurately forecast and control as-built mechanical properties. This approach enables digital qualification of part-specific microstructures and streamlines LPBF standardization. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Other, Other |