

Laser Powder Bed Fusion
This study explores the in-situ characterization of powder layer thickness and thermal transport properties in LPBF additive manufacturing through real-time infrared thermographic inspection. A infrared thermal camera records the temperature history of the powder surface immediately following the deposition of a new layer by the recoating system. As thermal energy diffuses from the underlying solid part, the temperature of the overlying powder layer increases. Informed by one-dimensional modeling of this heat-up process, experiments demonstrate the correlation between parameterized thermal history, powder layer thickness, and thermal conductivity. A neural network, trained on the parameterized thermal history, further enhances this correlation and is utilized to predict part distortion in unsupported structures. This method detects significant part distortion several layers before the part breaches the powder layer and interferes with the recoating process. The proposed approach can be automated to prevent catastrophic recoater collisions or abrasion of soft wipers and holds potential for in-situ monitoring of local powder layer properties. Additionally, this method aims to expedite the simulation of temperature and stress fields, ultimately contributing to the development of digital twins in additive manufacturing.



Publications
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"In-situ infrared thermographic inspection for local powder layer thickness measurement in laser powder bed fusion" Liu, T., Lough, C. S., Sehhat, H., Ren, Y. M., Christofides, P. D., Kinzel, E. C., & Leu, M. C. Additive Manufacturing, 55, 102873. 2022.
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"In-Situ Infrared Thermographic Measurement of Powder Properties in Laser Powder Bed" Liu, T., Kinzel, E. C., & Leu, M. C. 2022 International Solid Freeform Fabrication Symposium, 1402-1411. 2022.
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"Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared imaging thermal feature porosity probability maps" Lough, C. S., Liu, T., Wang, X., Brown, B., Landers, R. G., Bristow, D. A., Drallmeier, J. A., & Kinzel, E. C. Journal of Materials Processing Technology, 302, 117473. 2022.
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"Finite element modeling of direct metal laser solidification process: Sensor data replication and use in defect detection and data reduction via machine learning" Ren, Y. M., Zhang, Y., Ding, Y., Liu, T., Lough, C. S., Leu, M. C., Kinzel, E. C., & Christofides, P. D. Chemical Engineering Research and Design, 171, 254–267. 2021.
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"In-Situ Thermographic Inspection for Laser Powder" Liu, T., Lough, C. S., Sehhat, H., Huang, J., Kinzel, E. C., & Leu, M. C. 2021 International Solid Freeform Fabrication Symposium, 209-307. 2021.