Skip to main content
Log in

Analytical model of milling forces prediction in five-axis milling process

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In the process of the five-axis milling process, due to the changing of the cutter-workpiece engagement area and instantaneous uncut chip thickness, five-axis milling forces prediction is difficult compared with three-axis forces prediction. This study proposed a new analytical method to predict milling force in five-axis milling. Compared with the mechanistic calibration method and experiment method, this method predicts the cutting force accurately, does not need experiments, and only needs to know the input parameters, such as tool parameters, workpiece parameters, and cutting conditions. The effect of lead angle and tilt angle is analyzed by theoretical simulation. The correctness of the prediction model is verified by experiments under different conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Arrazola PJ, Özel T, Umbrello D, Davies M, Jawahir IS (2013) Recent advances in modelling of metal machining processes. CIRP Ann Manuf Technol 62:695–718

    Article  Google Scholar 

  2. Altintas Y, Kersting P, Biermann D, Budak E, Denkena B, Lazoglu I (2014) Virtual process systems for part machining operations. CIRP Ann Manuf Technol 63(2):585–605

    Article  Google Scholar 

  3. Tunc LT, Budak E (2009) Extraction of 5-axis milling conditions from CAM data for process simulation. Int J Adv Manuf Technol 43:538–550

    Article  Google Scholar 

  4. Zhu R, Kapoor SG, DeVor RE (2001) Mechanistic modeling of the ball end milling process for five-axis machining of free-form surfaces. J Manuf Sci Eng 123(3):369–379

    Article  Google Scholar 

  5. Sun Y, Guo Q (2011) Numerical simulation and prediction of cutting forces in five-axis milling processes with cutter run-out. Int J Mach Tools Manuf 51:806–815

    Article  Google Scholar 

  6. Li Z-L, Jin-Bo X-ZN, Wang L-MZ (2015) Mechanistic modeling of five-axis machining with a general end mill considering cutter runout. Int J Mach Tools Manuf 96:67–79

    Article  Google Scholar 

  7. Zhu Z, Yan R, Peng F, Duan X, Zhou L, Song K, Guo C (2016) Parametric chip thickness model based cutting forces estimation considering cutter runout of five-axis general end milling. Int J Mach Tools Manuf 101:35–51

    Article  Google Scholar 

  8. Duan X, Peng F, Yan R, Zhu Z, Huang K, Li B (2016) Estimation of cutter deflection based on study of cutting force and static flexibility. J Manuf Sci Eng 138(4):041001

    Article  Google Scholar 

  9. Guo M, Wei Z, Wang M (2018) An identification model of cutting force coefficients for five-axis ball-end milling. Int J Adv Manuf Technol 99:937–949

    Article  Google Scholar 

  10. Gdula M, Burek J, Zylka L, Plodzien M (2018) Five-axis milling of sculptured surfaces of the turbine blade. Aircr Eng Aerosp Technol 90(1):146–157

    Google Scholar 

  11. Ghorbani M, Movahhedy MR (2019) Extraction of surface curvatures from tool path data and prediction of cutting forces in the finish milling of sculptured surfaces. J Manuf Process 45:273–289

    Article  Google Scholar 

  12. Lin Z, Deng B, Peng F et al (2020) Semi-analytic modelling of cutting forces in micro ball-end milling of NAK80 steel with wear-varying cutting edge and associated nonlinear process characteristics. Int J Mech Sci 169:105343. https://doi.org/10.1016/j.ijmecsci.2019.105343

    Article  Google Scholar 

  13. Budak E, Altintas Y, Armarego EJA (1996) Prediction of milling force coefficients from orthogonal cutting data. J Manuf Sci Eng 118:216–224

    Article  Google Scholar 

  14. Fontaine M, Devillez A, Moufki A, Dudzinski D (2006) Predictive force model for ball-end milling and experimental validation with a wavelike form machining test. Int J Mach Tools Manuf 46:367–380

    Article  Google Scholar 

  15. Fu Z, Yang W, Wang X, Leopold J (2016) An analytical force model for ball-end milling based on a predictive machining theory considering cutter runout. Int J Adv Manuf Technol 84:2449–2460

    Article  Google Scholar 

  16. Zhou R, Yang W, Yang K (2016) Force prediction models for helical end milling of nickel-aluminum bronze. Int J Adv Manuf Technol 86:1487–1498

    Article  Google Scholar 

  17. Zhou R, Yang W (2019) Analytical modeling of machining-induced residual stresses in milling of complex surface. Int J Adv Manuf Technol 105:565–577

    Article  Google Scholar 

Download references

Funding

This study is supported by the Major State Basic Research Development Program of China (973 Program, Grant No.2014CB046704) and the Starting Research Fund from the Hubei University of Arts and Science.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ruihu Zhou.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, R. Analytical model of milling forces prediction in five-axis milling process. Int J Adv Manuf Technol 108, 3045–3054 (2020). https://doi.org/10.1007/s00170-020-05582-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-020-05582-6

Keywords

Navigation