About this Abstract |
| Meeting |
2021 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2021)
|
| Symposium
|
Special Session
|
| Presentation Title |
In-situ Detection and Prediction of Porosity in Laser Powder Bed Fusion Using Dual-wavelength Pyrometry |
| Author(s) |
Ziyad M. Smoqi, Aniruddha Gaikwad, Benjamin Bevans, Md Humaun Kobir, Alex Riensche, James Craig, Alan Abul-Haj, Alonso Peralta-Duran, Prahalada Rao |
| On-Site Speaker (Planned) |
Ziyad M. Smoqi |
| Abstract Scope |
Flaws, such as porosity and voids in the parts processed using laser powder bed fusion (LPBF) have a deleterious effect on mechanical properties. Accordingly, the objective of this research is the in-situ monitoring and detection of porosity formation in LPBF. To realize this objective, we use meltpool temperature and shape profiles captured using a dual-wavelength imaging pyrometer (Stratonics, ThermaViz). A cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus alloy) was built under ten conditions of laser power (120 – 370 W) and scanning speeds (800 – 3780 mm/s). The part porosity was assessed offline using X-ray computed tomography. The porosity variation was correlated with the meltpool shape, temperature, and spatter characteristics obtained from the pyrometer using a variety of machine learning approaches. Results of prediction show that the level (severity) of porosity can be predicted with an accuracy exceeding 90% (statistical F-score). |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |