About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Presentation Title |
In-situ Monitoring and Prediction of Porosity in Laser Powder Bed Fusion using Physics-informed Meltpool Signature and Machine Learning |
Author(s) |
Ziyad M. Smoqi, Aniruddha Gaikwad, Benjamin Bevans, Md Humaun Kobir, James Craig, Alan Abul-Haj, Alonso Peralta, Prahalada Rao |
On-Site Speaker (Planned) |
Ziyad M. Smoqi |
Abstract Scope |
The goal of this research is the in-situ monitoring and detection of porosity formation in LPBF using a two-wavelength imaging pyrometer (ThermaViz). To realize this goal, a large cuboid of ATI 718Plus Alloy part (10 mm × 10 mm × 137 mm) was built under different conditions of laser powers and scanning speeds. During the process, meltpool temperature and shape measurements were acquired using the two-wavelength imaging pyrometer. The porosity analysis of the part was performed offline using X-ray computed tomography (XCT). The porosity in different segments of the part was correlated with physically relevant meltpool signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, using simple machine learning approaches. Both the severity of porosity and its type were predicted with an accuracy exceeding 95% (statistical F1-score). |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |