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An improved dynamic milling force coefficients identification method considering edge force

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Abstract

The identification of the dynamic coefficients is the key to realize accurate simulation of dynamic milling process. To enlarge the scope of dynamic simulation without ignoring edge force, an improved method is presented to calculate milling force coefficients. In this method, linear approximation of average milling force is integrated with multiple linear regressions by supposing that milling force coefficients are time invariant for small variation of feed rate. Therefore, both the shear coefficients and the edge coefficients can be calculated simultaneously. A comparison of simulated milling force with and without the edge force is illustrated and the result shows that the accuracy is higher if the edge force coefficients are considered. This method casts new light on fast and accurate simulation of the dynamic milling force in real industrial environment.

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References

  1. Jianwei Dang, Weihong Zhang, Yun yang and Min Wan, Cutting force modeling for flat end milling including bottom edge effect cutting, International journal of Machine Tools & Manufacture, 50(11) (2010) 986–997.

    Article  Google Scholar 

  2. G. Yucesan and Y. Altintas, Improved modeling of cutting force coefficients in peripheral milling, International Journal of Machine Tools & Manufacture, 34(4) (1994) 473–487.

    Article  Google Scholar 

  3. X. P. Li, J. Q. Zheng, Y. S. Wong and A. Y. C. Nee, An approach to theoretical modeling and simulation of face milling forces, Journal of Manufacturing Processes, 2(4) (2000) 225–240.

    Article  Google Scholar 

  4. M. Yang and H. Park, The prediction of cutting force in ballend milling, International Journal of Machine Tools & Manufacture, 31(1) (1991) 45–54.

    Article  Google Scholar 

  5. I. S. Kang, J. S. Kim, J. H. Kim, M. C. Kang and Y. W. Seo, A mechanistic model of cutting force in the micro end milling process, Journal of Materials Processing Technology, 187/188 (2007) 250–255.

    Article  Google Scholar 

  6. W. A. Kline, R. E. Devor and J. R. Linberg, The prediction of cutting forces in end milling with application to cornering cuts, International Journal of Machine Tool Design and Research, 22(1) (1982) 7–22.

    Article  Google Scholar 

  7. Y. Altintas, Manufacturing automation—Metal cutting mechanics, machine tool vibrations, and CNC design, Cambridge University Press, Cambridge, UK (2000).

    Google Scholar 

  8. S. Engin and Y. Altintas, Mechanics, dynamics of general milling cutters. Part I: helical end mills, International Journal of Machine Tools & Manufacture, 41(15) (2001) 2195–2212.

    Article  Google Scholar 

  9. A. Lamikiz, L. N. Lo’pez de Lacalle, J. A. Sa’nchez, M. A. Salgado, Cutting force estimation in sculptured surface milling, International Journal of Machine Tools & Manufacture, 44 (2004) 1511–1526.

    Article  Google Scholar 

  10. Min Liu, Lulu Jin, Qinglong An and Ming Chen, Study on cutting force coefficients in end milling die steel $Cr16Mo, Journal of Shanghai Jiao Tong University, 43(1) (2009) 25–29.

    Article  Google Scholar 

  11. Li Yin and Qiang Liu, Study on the identification of the milling force Parameter model based on partial least square regression and application, Mechanical Science And Technology, 24(3) (2005) 269–272.

    Google Scholar 

  12. George W. Collins, II. Fundamental numerical methods and data Analysis. Case Western Reserve University, Cleveland, USA (2003).

    Google Scholar 

  13. Donald. E. Myers, Spatial interpolation: an overview. Geoderma, 62 (1994) 17–28.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300072, China

    Guofeng Wang, Dongbiao Peng, Xuda Qin & Yinhu Cui

Authors
  1. Guofeng Wang
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  2. Dongbiao Peng
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  3. Xuda Qin
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  4. Yinhu Cui
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Corresponding author

Correspondence to Guofeng Wang.

Additional information

Recommended by Associate Editor Song Min Yoo.

Guofeng Wang is currently an associate professor in School of Mechanical Engineering, Tianjin University, China. He received his PhD degree from Tianjin University, China, in March 2002. His research interests include dynamic modeling and condition monitoring of machining process.

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Wang, G., Peng, D., Qin, X. et al. An improved dynamic milling force coefficients identification method considering edge force. J Mech Sci Technol 26, 1585–1590 (2012). https://doi.org/10.1007/s12206-012-0306-x

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  • DOI: https://doi.org/10.1007/s12206-012-0306-x

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