Applied Machine Tool Data Condition to Predictive Smart Maintenance by Using Artificial Intelligence-Reference-Cited by-同舟云学术

Applied Machine Tool Data Condition to Predictive Smart Maintenance by Using Artificial Intelligence

Published:2022 Issue: Volume: Page:584-596
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Singh Chaitanya^ORCID,Rao M. S. Srinivasa,Mahaboobjohn Y. M.,Kotaiah Bonthu,Kumar T. Rajasanthosh

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07012-9_49

Reference30 articles.

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3. Aramesh, M., Attia, M., Kishawy, H., Balazinski, M.: Estimating the remaining useful tool life of worn tools under different cutting parameters: a survival life analysis during turning of titanium metal matrix composites (Ti-MMCs). CIRP J. Manuf. Sci. Technol. 12, 35–43 (2016)

4. Wu, R., Huang, L., Zhou, H.: RHKV: an RDMA and HTM friendly key-value store for data-intensive computing. Future Gener. Comput. Syst. 92, 162–177 (2019)

5. Zhang, W., Yang, D., Wang, H.: Data-driven methods for predictive maintenance of industrial equipment: a survey. IEEE Syst. J. 13, 2213–2227 (2019)

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