Funder
Independent Training and Innovation Team Project of Jinan Science and Technology Bureau
National Natural Science Foundation of China
Natural Science Foundation for Young Scientists of Hebei Province
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Polymers and Plastics,Mechanical Engineering,Mechanics of Materials
Reference47 articles.
1. Olsson M, Bushlya V, Lenrick F et al (2021) Evaluation of tool wear mechanisms and tool performance in machining single-phase tungsten. Int J Refract Met H 94:105379. https://doi.org/10.1016/j.ijrmhm.2020.105379
2. Zhuang K, Shi Z, Sun Y et al (2021) Digital twin-driven tool wear monitoring and predicting method for the turning process. Symmetry 13(8):1438. https://doi.org/10.3390/sym13081438
3. Denis B, Luiz CF, Bertrand SR (2020) Prediction of PCBN tool life in hard turning process based on the three-dimensional tool wear parameter. Int J Adv Manuf Tech 106(1):779–790
4. Marani M, Zeinali M, Kouam J et al (2020) Prediction of cutting tool wear during a turning process using artificial intelligence techniques. Int J Adv Manuf Tech 111(1):505–515
5. Seemuang N, McLeay T, Slatter T (2016) Using spindle noise to monitor tool wear in a turning process. Int J Adv Manuf Tech 86(12):2781–2790
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