Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model

Yuqing Zhanga Advanced Design and Systems Engineering Department, City University of Hong Kong, Hong Kong, Hong Kong

https://orcid.org/0000-0003-1086-0963 View further author information

Min Xiea Advanced Design and Systems Engineering Department, City University of Hong Kong, Hong Kong, Hong Kong;b Shenzhen Research Institute, City University of Hong Kong, Shenzhen, People’s Republic of ChinaView further author information

Yihai Hec School of Reliability and Systems Engineering, Beihang University, Beijing, People’s Republic of ChinaCorrespondence[email protected]

https://orcid.org/0000-0002-9110-2672 View further author information

Xiao Hanc School of Reliability and Systems Engineering, Beihang University, Beijing, People’s Republic of ChinaView further author information

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Sathish Kasilingam, Ruoyu Yang, Shubhendu Kumar Singh, Mojtaba A. Farahani, Rahul Rai & Thorsten Wuest. (2024) Physics-based and data-driven hybrid modeling in manufacturing: a review. Production & Manufacturing Research 12:1.
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Gyeongho Kim, Sang Min Yang, Sinwon Kim, Do Young Kim, Jae Gyeong Choi, Hyung Wook Park & Sunghoon Lim. (2023) A multi-domain mixture density network for tool wear prediction under multiple machining conditions. International Journal of Production Research 0:0, pages 1-20.
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Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model

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Capability-based remaining useful life prediction of machining tools considering non-geometry and tolerancing features with a hybrid model

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