Adaptive optimization of cutting parameters in milling industry considering dynamic tool wear in intelligent manufacturing driven by reinforcement learning

Author:

Gao Zhilie,Li Liang

Publisher

Springer Science and Business Media LLC

Reference20 articles.

1. Yongliang Z, Shuaishuai Z, Zhan Z, Tao Q (2021) Milling of weakly rigid parts based on MRF flexible auxiliary support. Mech Strength 43(4):868–873

2. Guangchao H, Pan Gaofeng Wu, Linhong WX (2018) Research on burr forming characteristics of ultrasonic micro milling. J Beijing Inst Technol 38(9):888–892

3. Mei Jiawei, Diaz OG, Axinte DA (2019) Modelling the unidirectional fibre composite milling force oscillations through capturing the influence of the stochastic fibre distributions. Comp Struct 226:111188.1-1111881.5

4. Jingwen Z, Qin Wenjin Mu, Yingjuan RP, Xing L, Yan C (2020) Comparative study on milling and grinding of carbon fiber composite materials. Diamond Abrasives Eng 40(4):76–80

5. Tm A, Ss B, Rr C, Nrs A, Ap D (2020) Tool condition monitoring techniques in milling process — a review. J Market Res 9(1):1032–1042

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