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Machining accuracy reliability evaluation of CNC machine tools based on the milling stability optimization

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Abstract

The machining accuracy reliability of machine tools has important practical significance for the quality of processed parts. In the milling process, the geometric errors and vibration errors are the two key error sources which severely decrease the machining accuracy reliability of machine tools. To ensure that machine tools can maintain high machining accuracy and reliability for a long time, the paper proposes a machining accuracy reliability evaluation method that considers both the geometric and vibration errors. Based on the milling dynamics theory and the full-discretization method (FDM), a four degrees of freedom (DOF) milling dynamics model of the tool-workpiece vibration system and a vibration error prediction model of the tool-workpiece system are established. The former is used for the milling stability prediction and the milling parameter optimization, while the latter is used for the vibration errors prediction. Utilizing the multi-body system (MBS) theory, a comprehensive error model considering both the geometric and vibration errors is established to explain the influence of errors on machining accuracy. Based on the Monte Carlo simulation of directional importance sampling (DIS-MCS), a machining accuracy reliability model is proposed to evaluate the machining ability of machine tools. The method is applied to a five-axis CNC machine tool, and the application results explain the correctness and competitiveness of the proposed method. It can realize the milling parameter optimization, the vibration error prediction of the tool-workpiece system, and the machining accuracy reliability evaluation of machine tools.

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Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was sponsored by the National Natural Science Foundation of China (grant no. 51905334, grant no.51975019), Shanghai Sailing Program (grant no.19YF1418600, grant no.19YF1452400, grant no.19YF1418900), and the National Science and Technology Major Project (grant no.2019ZX04001001).

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Authors and Affiliations

  1. Logistics Engineering College, Shanghai Maritime University, Shanghai, 201306, China

    Ziling Zhang, Yujie Yang, Guowei Li, Cong Yue & Yongli Hu

  2. Yingtan Technical School, Yingtan 335000, Jiangxi, China

    Yin Qi

  3. Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, 100124, China

    Ying Li

Authors
  1. Ziling Zhang
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  2. Yujie Yang
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  3. Guowei Li
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  4. Yin Qi
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  5. Cong Yue
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  6. Yongli Hu
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  7. Ying Li
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Contributions

Ziling Zhang and Ying Li are responsible for providing overall research ideas; Ziling Zhang and Yujie Yang are responsible for the data simulation of the paper; Guowei Li, Yin Qi, and Ying Li are responsible for the measurement of machine tool error data, Cong Yue and Yongli Hu is responsible for experimental data analysis.

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Correspondence to Ying Li.

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Zhang, Z., Yang, Y., Li, G. et al. Machining accuracy reliability evaluation of CNC machine tools based on the milling stability optimization. Int J Adv Manuf Technol 124, 4057–4074 (2023). https://doi.org/10.1007/s00170-022-08832-x

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  • DOI: https://doi.org/10.1007/s00170-022-08832-x

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