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PUBLICATIONS

A meltpool prediction based scan strategy for powder bed fusion additive manufacturing

Published

Author(s)

Ho Yeung, Zhuo Yang, Yan Lu

Abstract

In this study a feedforward control method for laser powder bed fusion (LPBF) additive manufacturing (AM) process is demonstrated. It minimizes the meltpool variation by updating the scan strategy based on a data-driven predictive meltpool model. A rectangular pattern is scanned multiple times on a customized LPBF testbed. The meltpool is monitored in situ by a high-speed camera, optically aligned with the heating laser. Constant laser power is applied for the first scan, and its meltpool images are used to train the model and adjust the laser power for the following scans. The meltpool images from these scans are compared, and a significant reduction in meltpool variation is achieved.
Citation
Additive Manufacturing
Volume
35
Pub Type
Journals

Download Paper

https://doi.org/10.1016/j.addma.2020.101383
Local Download

Keywords

Additive Manufacturing, LPBF, Scan strategy, Machine learning
Manufacturing and Additive manufacturing

Citation

Yeung, H. , Yang, Z. and Lu, Y. (2020), A meltpool prediction based scan strategy for powder bed fusion additive manufacturing, Additive Manufacturing, [online], https://doi.org/10.1016/j.addma.2020.101383 (Accessed April 25, 2024)

Created June 7, 2020, Updated October 7, 2020