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Condition monitoring Meta-learning Process control
Number of items: 3.

Condition monitoring

Li, Yingguang, Liu, Changqing, Hua, Jiaqi, Gao, James ORCID logoORCID: https://orcid.org/0000-0001-5625-3654 and Maropoulos, Paul (2019) A novel method for accurately monitoring and predicting tool wear under varying cutting conditions based on meta-learning. CIRP Annals ‐ Manufacturing Technology, 68 (1). pp. 487-490. ISSN 0007-8506 (doi:10.1016/j.cirp.2019.03.010)

Meta-learning

Li, Yingguang, Liu, Changqing, Hua, Jiaqi, Gao, James ORCID logoORCID: https://orcid.org/0000-0001-5625-3654 and Maropoulos, Paul (2019) A novel method for accurately monitoring and predicting tool wear under varying cutting conditions based on meta-learning. CIRP Annals ‐ Manufacturing Technology, 68 (1). pp. 487-490. ISSN 0007-8506 (doi:10.1016/j.cirp.2019.03.010)

Process control

Li, Yingguang, Liu, Changqing, Hua, Jiaqi, Gao, James ORCID logoORCID: https://orcid.org/0000-0001-5625-3654 and Maropoulos, Paul (2019) A novel method for accurately monitoring and predicting tool wear under varying cutting conditions based on meta-learning. CIRP Annals ‐ Manufacturing Technology, 68 (1). pp. 487-490. ISSN 0007-8506 (doi:10.1016/j.cirp.2019.03.010)

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