Multimodal deep learning for predicting the choice of cut parameters in the milling process
In this paper, we use multimodal deep learning to predict the choice of optimal cutting parameters (cutting speed, depth of cut, and feed rate per tooth) and the appropriate cutting tool for reproducing an existent piece of the same surface state, considering the footprints left by the cutting tool....
Main Authors: | Cheick Abdoul Kadir A Kounta, Bernard Kamsu-Foguem, Farid Noureddine, Fana Tangara |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2022-11-01
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Series: | Intelligent Systems with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305322000503 |
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