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Time-varying analytical model of ball-end milling tool wear in surface milling

Abstract

The quality of a workpiece depends on the time-varying characteristics of the tool performance. Tool wear is an important factor that affects the serviceability of a tool. However, most existing models do not fully contain the tool design and processing parameters and do not focus on the time-varying characteristics of wear. In this paper, the wear distribution characteristics of a ball-end mill were investigated by analysing the position function in the milling life model, and the geometric model of the wear volume was proposed based on the principle of calculus. By geometric and physical modelling, the tool design and machining parameters were completely introduced in the model, and the time variable is introduced when solving the wear rate. After the models and assumptions are validated, the factors affecting wear are cross-analysed and discussed through simulation. Wear models including time variables, tool design, and milling parameters are obtained, which can be used directly for tool design and analysis. This research provides a basis for the tool analytical design.

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References

  1. 1.

    Abele E, Hasenfratz C, Bücker M (2017) Modeling of process forces with respect to technology parameters and tool wear in milling Ti6Al4V. Prod Eng 11(3):285–294

  2. 2.

    Yue C, Gao H, Liu X, Liang SY (2018) Part functionality alterations induced by changes of surface integrity in metal milling process: a review. Appl Sci 8:2550

  3. 3.

    Eshi U (1982) Cutting and grinding processing. Mechanical Industry Press, China

  4. 4.

    Ning L, Veldihuis SC (2006) Mechanistic modeling of ball end milling including tool wear. J Manuf Process 8(1):21–28

  5. 5.

    Zhang C, Zhou L, An L (2008) Modeling and error compensation for tool wear of ball-end milling cutter. Aust J Mech Eng 44(2):207–212

  6. 6.

    Zhang C, Zhou L (2013) Modeling of tool wear for ball end milling cutter based on shape mapping. Int J Interact Des Manuf 7(3):171–181

  7. 7.

    Khan MR (2011) Geometric modeling, design and analysis of custom-engineered milling cutters. Jabalpur

  8. 8.

    Huang Y, Liang SY (2004) Modeling of CBN tool flank wear progression in finish hard turning. J Manuf Sci Eng 126(1):98–106

  9. 9.

    Li KM, Liang SY (2012) Flank wear model for near dry turning under built-up edge effect. J Chn Mech Eng 33(2):123–132

  10. 10.

    Teitenberg TM, Bayoumi AE, Yucesan G (1992) Tool wear modeling through an analytic mechanistic model of milling processes. Wear 154(2):287–304

  11. 11.

    Okamoto Y, Yazawa T, Kato T, Nishida K, Moriyama S, Maeda Y et al (2017) Study on tool wear in-process estimation for ball end mill using rotation control air turbine spindle. Key Eng Mater 749:94–100

  12. 12.

    Mou T (2009) Research on tool wear of high speed milling Ti6Al4V. J Shandong Univ, Jinan

  13. 13.

    Jiang B, Zheng M, Yang S (2003) Establishment of mathematical model for service life of ball-end milling cutter. Manuf Technol Mach Tools 8:9–11

  14. 14.

    Li Y, Deng J, Shi L (2007) Tool materials for high speed machining of titanium alloys. Manuf Technol Mach Tools 8:24–27

  15. 15.

    Sun Y, Sun J, Li J (2016) Finite element prediction analysis of tool wear in titanium milling. Aust J Mech Eng 52:193–201

  16. 16.

    Rabinowicz E, Dunn LA, Russell PG (1961) A study of abrasive wear under three-body conditions. Wear 4(5):345–355

  17. 17.

    Lee M (1983) High temperature hardness of tungsten carbide. Metall Trans A 14:1625–1629

  18. 18.

    Guo B, Zhang L, Cao L, Zhang T, Jiang F, Yan L (2018) The correction of temperature-dependent Vickers hardness of cemented carbide base on the developed high-temperature hardness tester. J Mater Process Technol 255:426–433

  19. 19.

    Milman YV, Luyckx S, Northrop IT (1999) Influence of temperature, grain size and cobalt content on the hardness of WC–Co alloys. Int J Refract Met Hard Mater 17:39–44

  20. 20.

    Genghuang H (2013) Research on high-efficiency cutting and tool technology for large barrel sections. Harbin Univ Sci Technol, Harbin

  21. 21.

    Milman YV, Chugunova S, Goncharuck V, Luyckx S, Northrop IT (1997) Low and high temperature hardness of WC-6 wt%Co alloys. Int J Refract Met Hard Mater 15:97–101

  22. 22.

    Kramer BM, Judd PK (1985) Computational design of wear coatings. J Vac Sci Technol A Vac Surf Films 3:2439–2444

  23. 23.

    Tang L, Xie L, Ma S et al (2010) Experimental research on machining TC4 titanium alloy engine blade ball knife. Manuf Technol Mach Tools 2:92–94

  24. 24.

    Fick A (1995) On liquid diffusion. J Membr Sci 100(1):33–38

  25. 25.

    Miller FP, Vandome AF, McBrewster J (2010) Fick’s laws of diffusion. Alphascript Publishing, Germany

  26. 26.

    Ezugwu EO, Wang ZM (1997) Titanium alloys and their machinability—a review. J Mater Process Technol 68:262–274

  27. 27.

    Sui SC, Feng PF, Mou WP (2016) Temperature modeling analysis for milling of titanium alloy. Key Eng Mater 693:928–935

  28. 28.

    Li L, Chang H, Wang M, Zuo DW, He L (2004) Temperature measurement in high speed milling Ti6Al4V. Key Eng Mater 259:804–808

  29. 29.

    Ji S, Ni J, Zhan B et al (2016) Orthogonal experimental study on milling temperature of TC4 titanium alloy. Manuf Technol Mach Tools 2:91–93

  30. 30.

    Yang Y, Zhao W, Li L et al (2014) Experimental study on cutting force and cutting temperature of Ti6Al4V titanium alloy in large feed milling. Aviat Precis Manufac Technol 50:34–37

  31. 31.

    Cui D, Zhang D, Wu B, Luo M (2017) An investigation of tool temperature in end milling considering the flank wear effect. Int J Mech Sci 131:613–624

  32. 32.

    Han M, Li Y, Zhao W (2008) Experimental study on cutting temperature of Ti6Al4V titanium alloy during high speed cutting. Tool Technol 42:10–13

  33. 33.

    Attanasio A, Ceretti E, Rizzuti S, Umbrello D, Micari F (2008) 3D finite element analysis of tool wear in machining. CIRP Ann Manuf Technol 57:61–64

  34. 34.

    Anto T, Anil PM (2013) An analysis on the influence of temperature on the sliding wear of components finished by grinding and milling processes. Proc Int Conf Energ Effic Technol Sustain

  35. 35.

    Komanduri R (1982) Some clarifications on the mechanics of chip formation when machining titanium alloys. Wear 76:15–34

  36. 36.

    Jiang H (2005) A cobalt diffusion based model for predicting crater wear of carbide tools in machining titanium alloys. J Eng Mater Technol 127:136–144

  37. 37.

    Yue C, Gao H, Liu X, Liang SY, Wang L (2019) A review of chatter vibration research in milling. Chin J Aeronaut 32:1–28

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Correspondence to Xianli Liu.

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Zhao, Z., Liu, X., Yue, C. et al. Time-varying analytical model of ball-end milling tool wear in surface milling. Int J Adv Manuf Technol (2020). https://doi.org/10.1007/s00170-019-04783-y

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Keywords

  • Ball-end milling tool
  • Surface milling
  • Time-varying analytical model of wear modelling
  • Wear