A second-order semi-discretization method for the efficient and accurate stability prediction of milling process

ORIGINAL ARTICLE

Abstract

Due to the high computational accuracy and good applicability with a low complexity of algorithm, semi-discretization method has a significant application for predicting milling stability, but to some extent it has some limitations in computational efficiency. Based on the Newton interpolation polynomial and an improved precise time-integration (PTI) algorithm, a second-order semi-discretization method for efficiently and accurately predicting the stability of the milling process is proposed. In the method, the milling dynamic system considering the regenerative effect is first approximated by a time-periodic delayed-differential equation (DDE) and then reformulated in state-space form. After discretizing the time period into a finite number of time intervals, the equation is integrated on each discrete time interval. In order to improve the approximation accuracy of the time-delay item, a second-order Newton interpolation polynomial is utilized instead of a linear function used in the original first-order semi-discretization method (SDM). Next, with a rapid matrix computation technique, an improved precise time-integration algorithm is employed to calculate the resulting exponential matrices efficiently. Finally, transition matrix of the system is constructed over the discretization period and the milling stability boundary is determined by Floquet theory. Compared with the typical discretization methods, the proposed method indicates a faster convergence rate. Further, two benchmark examples are given to validate the effectiveness of the proposed method from the aspects of computational efficiency and accuracy.

Keywords

Milling stability Second-order semi-discretization method Newton interpolation Precise time-integration Floquet theory 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Altintas Y (2012) Manufacturing automation, 2nd edn. Cambridge University Press, CambridgeGoogle Scholar
  2. 2.
    Tobias SA (1965) Machine tool vibration. Blackie and Sons Ltd, New YorkGoogle Scholar
  3. 3.
    Li ZJ, Fang FZ, Gong H, Zhang XD (2013) Review of diamond-cutting ferrous metals. Int J Adv Manuf Technol 68(5–8):1717–1731Google Scholar
  4. 4.
    Quintana G, Ciurana J, Teixidor D (2008) A new experimental methodology for identification of stability lobes diagram in milling operations. Int J Mach Tools Manuf 48(15):1637–1645CrossRefGoogle Scholar
  5. 5.
    Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. CIRPAnn Manuf Technol 44(1):357–362CrossRefGoogle Scholar
  6. 6.
    Bayly PV, Mann BP, Schmitz TL, Peters DA, Stepan G and Insperger T (2002) Effects of radial immersion and cutting direction on chatter instability in end milling. In ASME 2002 International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers pp: 351–363Google Scholar
  7. 7.
    Stepan G, Szalai R, Mann BP, Bayly PV, Insperger T, Gradisek J, Govekar E (2005) Nonlinear dynamics of high-speed milling—analyses, numerics, and experiments. J Vib Acoust 127(2):197–203CrossRefGoogle Scholar
  8. 8.
    Budak E, Altintas Y (1998) Analytical prediction of chatter stability in milling —part I: general formulation. J Dyn Syst 120(1):22–30CrossRefGoogle Scholar
  9. 9.
    Merdol SD, Altintas Y (2004) Multi-frequency solution of chatter stability for low immersion milling. J Manuf Sci Eng 126(3):459–466CrossRefGoogle Scholar
  10. 10.
    Altintas Y, Shamoto E, Lee P, Budak E (1999) Analytical prediction of stability lobes in ball end milling. J Manuf Sci Eng 121(4):586–592CrossRefGoogle Scholar
  11. 11.
    Altıntaş Y, Engin S, Budak E (1999) Analytical stability prediction and design of variable pitch cutters. J Manuf Sci Eng 121(2):173–178CrossRefGoogle Scholar
  12. 12.
    Jensen SA, Shin YC (1999) Stability analysis in face milling operations, part 1: theory of stability lobe prediction. J Manuf Sci Eng 121(4):600–605CrossRefGoogle Scholar
  13. 13.
    Jensen SA, Shin YC (1999) Stability analysis in face milling operations, part 2: experimental validation and influencing factors. J Manuf Sci Eng 121(4):606–614CrossRefGoogle Scholar
  14. 14.
    Ozlu E, Budak E (2007) Analytical modeling of chatter stability in turning and boring operations—part I: model development. J Manuf Sci Eng 129(4):726–732CrossRefGoogle Scholar
  15. 15.
    Ozlu E, Budak E (2007) Analytical modeling of chatter stability in turning and boring operations—part II: experimental verification. J Manuf Sci Eng 129(4):733–739CrossRefGoogle Scholar
  16. 16.
    Tlusty J, Zaton W, Ismail F (1983) Stability lobes in milling. CIRP Annals-Manuf Technol 32(1):309–313CrossRefGoogle Scholar
  17. 17.
    Campomanes ML, Altintas Y (2003) An improved time domain simulation for dynamic milling at small radial immersions. J Manuf Sci Eng 125(3):416–422CrossRefGoogle Scholar
  18. 18.
    Bayly PV, Halley JE, Mann BP, Davies MA (2003) Stability of interrupted cutting by temporal finite element analysis. J Manuf Sci Eng 125(2):220–225CrossRefGoogle Scholar
  19. 19.
    Butcher EA, Nindujarla P and Bueler E (2005) Stability of up-and down-milling using Chebyshev collocation method. In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers pp: 841–850Google Scholar
  20. 20.
    Yan Z, Liu Z, Wang X, Liu B, Luo Z and Wang D (2016) Stability prediction of thin-walled workpiece made of Al7075 in milling based on shifted Chebyshev polynomials. Int J Adv Manuf Technol pp:1–10Google Scholar
  21. 21.
    Insperger T, Stepan G (2002) Semi-discretization method for delayed systems. Int J Numer Methods Biomed Eng 55(5):503–518MathSciNetCrossRefMATHGoogle Scholar
  22. 22.
    Insperger T, Stépán G (2004) Updated semi-discretization method for periodic delay-differential equations with discrete delay. Int J Numer Methods Eng 61(1):117–141MathSciNetCrossRefMATHGoogle Scholar
  23. 23.
    Insperger T (2010) Full-discretization and semi-discretization for milling stability prediction: some comments. Int J Mach Tools Manuf 50(7):658–662MathSciNetCrossRefGoogle Scholar
  24. 24.
    Dombovari Z, Stepan G (2012) The effect of helix angle variation on milling stability. J Manuf Sci Eng 134(5):051015CrossRefGoogle Scholar
  25. 25.
    Dombovari Z, Munoa J, Stepan G (2012) General milling stability model for cylindrical tools. Procedia CIRP 4:90–97CrossRefGoogle Scholar
  26. 26.
    Dombovari Z, Altintas Y, Stepan G (2010) The effect of serration on mechanics and stability of milling cutters. J Manuf Sci Eng 50(6):511–520Google Scholar
  27. 27.
    Moradi H, Vossoughi G, Movahhedy MR (2013) Experimental dynamic modelling of peripheral milling with process damping, structural and cutting force nonlinearities. J Sound Vib 332(19):4709–4731CrossRefGoogle Scholar
  28. 28.
    Wan M, Zhang WH, Dang JW, Yang Y (2010) A unified stability prediction method for milling process with multiple delays. Int J Mach Tools Manuf 50(1):29–41CrossRefGoogle Scholar
  29. 29.
    Wan M, Altintas Y (2014) Mechanics and dynamic of thread milling process. Int J Mach Tools Manuf 87:16–26CrossRefGoogle Scholar
  30. 30.
    Insperger T, Stepan G (2011) Semi-discretization for time-delay systems: stability and engineering applications. Springer, NewYorkCrossRefMATHGoogle Scholar
  31. 31.
    Seguy S, Insperger T, Arnaud L (2010) On the stability of high-speed milling with spindle speed variation. Int J Adv Manuf Technol 48:883–895CrossRefGoogle Scholar
  32. 32.
    Hartung F, Insperger T, Stépán G, Turi J (2006) Approximate stability charts for milling processes using semi-discretization. Appl Math Comput 174(1):51–73MathSciNetMATHGoogle Scholar
  33. 33.
    Xie Q, Zhang Q (2012) Stability predictions of milling with variable spindle speed using an improved semi-discretization method. Math Comput Simulat 85:78–89MathSciNetCrossRefGoogle Scholar
  34. 34.
    Elías-Zúñiga A, Pacheco-Bolívar J, Araya F, Martínez-López A, Martínez-Romero O, Rodríguez CA (2009) Stability predictions for end milling operations with a nonlinear cutting force model. J Manuf Sci Eng 131(6):064504CrossRefGoogle Scholar
  35. 35.
    Ahmadi K, Ismail F (2011) Analytical and stability lobes including nonlinear process damping effect on machining chatter. Int J Mach Tools Manufacture 51(4):296–308CrossRefGoogle Scholar
  36. 36.
    Ahmadi K, Ismail F (2012) Modeling chatter in peripheral milling using the semi discretization method. CIRP Annals-Manuf Technol 5(2):77–86CrossRefGoogle Scholar
  37. 37.
    Zatarain M, Munoa J, Peigné G, Insperger T (2006) Analysis of the influence of mill helix angle on chatter stability. CIRP Annals-Manuf Technol 55(1):365–368CrossRefGoogle Scholar
  38. 38.
    Insperger T, Gradišek J, Kalveram M, Stépán G, Winert K, Govekar E (2006) Machine tool chatter and surface location error in milling processes. J Manuf Sci Eng 128(4):913–920CrossRefGoogle Scholar
  39. 39.
    Dong XF, Zhang WM, Deng S (2015) The reconstruction of a semi-discretization method for milling stability prediction based on Shannon standard orthogonal basis. Int J Adv Manuf Technol pp: 1–11Google Scholar
  40. 40.
    Ding Y, Zhu LM, Zhang XJ, Ding H (2010) A full-discretization method for prediction of milling stability. Int J Mach Tools Manuf 50(5):502–509CrossRefGoogle Scholar
  41. 41.
    Ding Y, Zhu LM, Zhang XJ, Ding H (2010) Second-order full-discretization method for milling stability prediction. Int J Mach Tools Manuf 50(10):926–932CrossRefGoogle Scholar
  42. 42.
    Quo Q, Sun YW, Jiang Y (2012) On the accurate calculation of milling stability limits using third-order full-discretization method. Int J Mach ToolsManuf 62:61–66CrossRefGoogle Scholar
  43. 43.
    Liu Y, Zhang D, Wu B (2012) An efficient full-discretization method for prediction of milling stability. Int J Mach Tools Manuf 63:44–48CrossRefGoogle Scholar
  44. 44.
    Ozoegwu CG (2014) Least squares approximated stability boundaries of milling process. Int J Mach Tools Manuf 79:24–30CrossRefGoogle Scholar
  45. 45.
    Ozoegwu CG, Omenyi SN, Ofochebe SM (2015) Hyper-third order full-discretization methods in milling stability prediction. Int J Mach Tools Manuf 92:1–9CrossRefGoogle Scholar
  46. 46.
    Ding Y, Zhu LM, Zhang XJ, Ding H (2011) Numerical integration method for prediction of milling stability. J Manuf Sci Eng 133(3):031005CrossRefGoogle Scholar
  47. 47.
    Zhang Z, Li HG, Meng G, Liu C (2015) A novel approach for the prediction of the milling stability based on the Simpson method. Int J Mach Tools Manuf 99:43–47CrossRefGoogle Scholar
  48. 48.
    Wan M, Ma YC, Zhang WH, Yang Y (2015) Study on the construction mechanism of stability lobes in milling process with multiple modes. Int J Adv Manuf Technol 79:589–603CrossRefGoogle Scholar
  49. 49.
    Tangjitsitcharoen S, Pongsathornwiwat N (2013) Development of chatter detection in milling processes. Int J Adv Manuf Technol 65:919–927CrossRefGoogle Scholar
  50. 50.
    Yang YQ, Liu Q, Zhang B (2014) Three-dimensional chatter stability prediction of milling based on the linear and exponential cutting force model. Int J Adv Manuf Technol 72:1175–1185CrossRefGoogle Scholar
  51. 51.
    Tang X, Peng F, Yan R, Gong Y, Li Y and Jiang L. (2016). Accurate and efficient prediction of milling stability with updated full-discretization method. Int J Adv Manuf Technol pp:1–12Google Scholar
  52. 52.
    Jin X, Sun Y, Guo Q, Guo D (2016) 3D stability lobe considering the helix angle effect in thin-wall milling. Int J Adv Manuf Technol 82(9–12):2123–2136CrossRefGoogle Scholar
  53. 53.
    Guo Q, Jiang Y, Zhao B, Ming P (2016) Chatter modeling and stability lobes predicting for non-uniform helix tools. Int J Adv Manuf Technol pp:1–16Google Scholar
  54. 54.
    Zhang X, Xiong C, Ding Y and Ding H (2016) Prediction of chatter stability in high speed milling using the numerical differentiation method. Int J Adv Manuf Technol pp:1–10Google Scholar
  55. 55.
    Zhang X, Zhang J, Pang B, Wu D, Zheng X, Zhao W (2016) An efficient approach for milling dynamics modeling and analysis with varying time delay and cutter runout effect. Int J Adv Manuf Technol pp:1–16Google Scholar
  56. 56.
    Xie Q (2016) Milling stability prediction using an improved complete discretization method. Int J Adv Manuf Technol 83(5–8):815–821CrossRefGoogle Scholar
  57. 57.
    Q. Guo, Y. Sun, Y. Jiang, Y. Yan, and P. Ming 2016 Determination of the stability lobes with multi-delays considering cutters helix angle effect for machining process, Proc. Inst. Mech. Eng. Part B J. Eng. ManufGoogle Scholar
  58. 58.
    Z. Li, Y. Sun, and D. Guo 2016 Chatter prediction utilizing stability lobes with process damping in finish milling of titanium alloy thin-walled workpiece, Int. J. Adv. Manuf. TechnolGoogle Scholar
  59. 59.
    Insperger T, Stépán G, Turi J (2008) On the higher-order semi-discretizations for periodic delayed systems. J Sound Vib 313(1–2):334–341CrossRefGoogle Scholar
  60. 60.
    Zhong WX, Williams FW (1994) A precise time step integration method. Proceedings of the Institution of Mechanical Engineers. Part C: J Mech Eng Sci 208(6):427–430Google Scholar
  61. 61.
    Tan S, Zhong W (2007) Precise integration method for Duhamel terms arising from non-homogenous dynamic systems. Chinese Journal of Theoretical and Applied Mechanics 39(3):374–381MathSciNetGoogle Scholar
  62. 62.
    Eksioglu C, Kilic ZM, Altintas Y (2012) Discrete-time prediction of chatter stability, cutting forces, and surface location errors in flexible milling systems. J Manuf Sci Eng 134(6):61006CrossRefGoogle Scholar
  63. 63.
    Yang Y, Zhang WH, Ma YC, Wan M (2016) Chatter prediction for the peripheral milling of thin-walled workpieces with curved surfaces. Int J Mach Tools Manuf 109:36–48CrossRefGoogle Scholar
  64. 64.
    Budak E, Tunc LT (2009) A new method for identification and modeling of process damping in machining. J Manuf Sci Eng 131(5):51019CrossRefGoogle Scholar
  65. 65.
    Ahmadi K, Altintas Y (2014) Identification of machining process damping using output-only modal analysis. ASME J Manuf Sci Eng 136(c):1–56Google Scholar
  66. 66.
    Wan M, Ma YC, Feng J, Zhang WH (2016) Study of static and dynamic ploughing mechanisms by establishing generalized model with static milling forces. Int J Mech Sci 114:120–131CrossRefGoogle Scholar
  67. 67.
    Altintas Y, Eynian M, Onozuka H (2008) Identification of dynamic cutting force coefficients and chatter stability with process damping. CIRP Ann—Manuf Technol 57(1):371–374CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  • Shanglei Jiang
    • 1
  • Yuwen Sun
    • 1
  • Xilin Yuan
    • 1
  • Weirui Liu
    • 1
  1. 1.Key Laboratory for Precision and Non-Traditional Machining Technology of the Ministry of EducationDalian University of TechnologyDalianChina

Personalised recommendations