Deep learning LSTM for predicting thermally induced geometric errors using rotary axes powers as input parameters

Huy Vu Ngoc, J. R. René Mayer and Elie Bitar-Nehme

Article (2022)

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Department:	Department of Mechanical Engineering
PolyPublie URL:	https://publications.polymtl.ca/50544/
Journal Title:	CIRP Journal of Manufacturing Science and Technology (vol. 37)
Publisher:	Elsevier Ltd
DOI:	10.1016/j.cirpj.2021.12.009
Official URL:	https://doi.org/10.1016/j.cirpj.2021.12.009
Date Deposited:	18 Apr 2023 14:59
Last Modified:	19 Jul 2023 12:03

Cite in APA 7:	Ngoc, H. V., Mayer, J. R. R., & Bitar-Nehme, E. (2022). Deep learning LSTM for predicting thermally induced geometric errors using rotary axes powers as input parameters. CIRP Journal of Manufacturing Science and Technology, 37, 70-80. https://doi.org/10.1016/j.cirpj.2021.12.009
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