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)
|
Presentation Title |
Prediction of Microstructure in LPBF using Part-level Thermal Simulations, In-process Sensor Data, and Machine Learning |
Author(s) |
Grant King |
On-Site Speaker (Planned) |
Grant King |
Abstract Scope |
The microstructure of parts manufactured using laser powder bed fusion (LPBF) are highly dependent on the thermal history (cooling rate) of the part during material deposition. Currently characterization of the microstructure must be completed post-processing.
In this research a combination of part-level thermal simulations and in-process sensor data (infrared thermal camera and meltpool imaging pyrometer) are used as inputs to machine learning models trained to predict the microstructure of a part (primary dendritic arm spacing). The approach is demonstrated in the context of twenty-one Inconel 718 parts of various shapes built under differing laser power and velocity settings. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |