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A study on the prediction of machining accuracy

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Abstract

The machining accuracy prediction has been widely studied in many manufacturing processes to achieve efficient control for production process. In this paper, a dynamic analysis model is proposed to develop the prediction model of machining accuracy. The dynamic analysis model has the advantage of high predictable power of the GM(1,1) model while at the same time utilizing the prediction power of the Markov chain model from stochastic process theory. Furthermore, Taylor approximation method is employed to enhance the prediction accuracy. The effectiveness of the proposed model is validated with a real case.

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Authors and Affiliations

  1. Department of System Design, Tokyo Metropolitan University, 191-0065, Hino City, Japan

    Guo-Dong Li & Shiro Masuda

  2. Faculty of Engineering, Kanagawa University, 221-8686, Yokohama City, Japan

    Daisuke Yamaguchi & Masatake Nagai

  3. Department of Microbiology, Hebei North University, Zhangjiakou City, 075000, China

    Chen-Hong Wang

Authors
  1. Guo-Dong Li
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  2. Shiro Masuda
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  3. Daisuke Yamaguchi
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  4. Masatake Nagai
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  5. Chen-Hong Wang
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Corresponding author

Correspondence to Guo-Dong Li.

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Li, GD., Masuda, S., Yamaguchi, D. et al. A study on the prediction of machining accuracy. Int J Adv Manuf Technol 43, 529–537 (2009). https://doi.org/10.1007/s00170-008-1728-6

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  • DOI: https://doi.org/10.1007/s00170-008-1728-6

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