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The optimization of the control logic of a redundant six axis milling machine

Author

Listed:
  • Antonio Caputi

    (Universita’ Degli Studi Di Bergamo)

  • Davide Russo

    (Universita’ Degli Studi Di Bergamo)

Abstract

The primary task of machine tools is simultaneously positioning and orienting the cutting tool with respect to the work piece. The mechanism must avoid positioning errors, and limit forces and torques required to the motors. A novel approach for combined design and control of manufacturing means is proposed in this work. The focus is on the optimization of the control logic of a redundant 6 axis milling machine, derived from the 5 axis milling machine by adding redundant degree of freedom to the work piece table. The new mechanism is able to fulfill a secondary task due to the introduction of redundancy. The proposed methodology sets as secondary task the minimization of the rotary motors torque, or the minimization of the norm of the positioning error. The control is based on the solution of a constrained optimization problem, where the constraints equations are the kinematic closure equations, and the objective function is the table motor torque or the positioning error of the tool tip. The implementation of this framework in the virtual machine model of the mechanism shows an improvement of the performances: actually, the introduction of a redundant axis allows the minimization of the torques and position errors.

Suggested Citation

  • Antonio Caputi & Davide Russo, 2021. "The optimization of the control logic of a redundant six axis milling machine," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1441-1453, June.
  • Handle: RePEc:spr:joinma:v:32:y:2021:i:5:d:10.1007_s10845-020-01705-8
    DOI: 10.1007/s10845-020-01705-8
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    References listed on IDEAS

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    1. Ziling Zhang & Ligang Cai & Qiang Cheng & Zhifeng Liu & Peihua Gu, 2019. "A geometric error budget method to improve machining accuracy reliability of multi-axis machine tools," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 495-519, February.
    2. Jianfeng Tao & Chengjin Qin & Dengyu Xiao & Haotian Shi & Xiao Ling & Bingchu Li & Chengliang Liu, 2020. "Timely chatter identification for robotic drilling using a local maximum synchrosqueezing-based method," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1243-1255, June.
    3. Qiang Cheng & Hongwei Zhao & Yongsheng Zhao & Bingwei Sun & Peihua Gu, 2018. "Machining accuracy reliability analysis of multi-axis machine tool based on Monte Carlo simulation," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 191-209, January.
    4. Ketai He & Qian Zhang & Yili Hong, 2019. "Profile monitoring based quality control method for fused deposition modeling process," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 947-958, February.
    5. Roman Stryczek, 2016. "A metaheuristic for fast machining error compensation," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1209-1220, December.
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