A two-stage tool wear prediction approach based on dual fusion of multi-feature and decision-making
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00170-023-12259-3.pdf
Reference47 articles.
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3. Liu C, Zheng P, Xu X (2021) Digitalisation and servitisation of machine tools in the era of Industry 4.0: a review. Int J Prod Res 1-33. https://doi.org/10.1080/00207543.2021.1969462
4. Wu D, Liu S, Zhang L, Terpenny J, Gao RX, Kurfess T, Guzzo JA (2017) A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing. J Manuf Syst 43:25–34. https://doi.org/10.1016/j.jmsy.2017.02.011
5. Wang J, Xie J, Zhao R, Zhang L, Duan L (2017) Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing. Robot Comput Integr Manuf 45:47–58. https://doi.org/10.1016/j.rcim.2016.05.010
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