The influence of supporting force on machining stability during mirror milling of thin-walled parts

  • Qile Bo
  • Haibo LiuEmail author
  • Meng Lian
  • Yongqing Wang
  • Kuo Liu


Mirror milling has been regarded as an effective way for large monolithic thin-walled parts machining. However, the supporting force not only improves the stiffness of the cutting point but also affects the dynamic behavior of the machining system. Essentially, the influence mechanism of supporting force on the mirror milling stability should be analyzed. Firstly, a 3-DOF dynamic system model has been developed considering the supporting head-workpiece interaction during mirror milling. And then, the evolution of modal parameters of thin-walled parts under different supporting forces is investigated with a series of impulse harmer tests, which will supply the dynamic parameters for the mirror milling stability lobes prediction using the full-discretization method. On this basis, the optimum supporting force can be determined according to the relationship of the limited cutting depth and the supporting force. At last, the analysis resulted was verified with a series of mirror milling slot test. From the comparison, the optimum supporting force could maintain the stable mirror milling and avoid excess deformation simultaneously.


Mirror milling Supporting force Machining stability Thin-walled parts 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


Funding information

This work is supported by National Basic Research Program Funding Agency of China (Grant No. 2014CB046604), NSFC-Liaoning Foundation (Grant No. U1608251), the Fundamental Research Funds for the Central Universities (Grant No. DUT17JC16), and Changjiang Scholar Program of Chinese Ministry of Education (No. T2017030).


  1. 1.
    Bao Y, Zhu XL, Kang RK, Dong ZG, Zhang B, Guo DM (2018) Optimization of support location in mirror-milling of aircraft skins. P I Mech Eng B-J Eng 232(9):1569–1576Google Scholar
  2. 2.
    Lan J, Lin B, Huang T, Xiao JL, Zhang XF, Fei JX (2017) Path planning for support heads in mirror-milling machining system. Int J Adv Manuf Technol 91:617–628CrossRefGoogle Scholar
  3. 3.
    Fang B, Devor RE, Kapoor SG (2002) Influence of friction damping on workpiece-fixture system dynamics and machining stability. J Manu Sci E-T ASME 124:226–233CrossRefGoogle Scholar
  4. 4.
    Zhao Y, Wang ZS, Wang H, Hao JM, Yu HD (2015) Stiffness analysis and optimization of supporting mechanism based on tricept for thin-walled part milling system. Proceedings of the 14th IFToMM World Congress 3:384–390Google Scholar
  5. 5.
    Esfandi N, Tsao TC (2017) Robot assisted machining of thin-walled structures. IFAC-Papers OnLine 50:14594–14599CrossRefGoogle Scholar
  6. 6.
    Fang B, Devor RE, Kapoor SG (2001) An elastodynamic model of frictional contact and its influence on the dynamics of a workpiece-fixture system. J Manu Sci E-T ASME 123:481–489CrossRefGoogle Scholar
  7. 7.
    Mahmud A, Mayer JRR, Baron L (2015) Determining the minimum clamping force by cutting force simulation in aerospace fuselage pocket machining. Int J Adv Manuf Technol 80:1751–1758CrossRefGoogle Scholar
  8. 8.
    Mahmud A, Mayer JRR, Baron L (2015) Magnetic attraction forces between permanent magnet group arrays in a mobile magnetic clamp for pocket machining. CIRP J of Manu Sci Tech 11:82–88CrossRefGoogle Scholar
  9. 9.
    Budak E, Altintas Y (1995) Analytical prediction of chatter stability in milling-part I: general formulation. J Dyn Syst-T ASME 120(1):22–30CrossRefGoogle Scholar
  10. 10.
    Altintas Y, Lee P (1998) Mechanics and dynamics of ball end milling. J Manu Sci E-T ASME 120(4):684–692CrossRefGoogle Scholar
  11. 11.
    Altintas Y, Lee P (1996) A general mechanics and dynamics model for helical end mills. CIRP Ann-Manuf Techn 45:59–64CrossRefGoogle Scholar
  12. 12.
    Sridhar R, Hohn RE, Long GW (1968) A stability algorithm for the general milling process: contribution to machine tool chatter research-7. J of Eng Indu 90:330–334CrossRefGoogle Scholar
  13. 13.
    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 87:251–266CrossRefGoogle Scholar
  14. 14.
    Turner S, Merdol D, Altintas Y, Ridgway K (2007) Modelling of the stability of variable helix end mills. Int J Mach Tools Manuf 47:1410–1416CrossRefGoogle Scholar
  15. 15.
    Altintas Y (2001) Analytical prediction of three dimensional chatter stability in milling. Jsme Int J C-Mech SY 44:717–723CrossRefGoogle Scholar
  16. 16.
    Fei JX, Lin B, Yan S, Zhang XF, Lan J, Dai SG (2017) Chatter prediction for milling of flexible pocket-structure. Int J Adv Manuf Technol 89:2721–2730CrossRefGoogle Scholar
  17. 17.
    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
  18. 18.
    Ozturk E, Budak E (2010) Dynamics and stability of five-axis ball-end milling. J Manu Sci E-T ASME 132:237–247Google Scholar
  19. 19.
    Dai YB, Li HK, Wei ZC, Zhang HY (2018) Chatter stability prediction for five-axis ball end milling with precise integration method. J Manuf Process 32:20–31CrossRefGoogle Scholar
  20. 20.
    Wang YQ, Bo QL, Liu HB, Hu L, Zhang H (2018) Mirror milling chatter identification using Q-factor and SVM. Int J Adv Manuf Technol 98:1163–1177CrossRefGoogle Scholar
  21. 21.
    Bayly PV, Mann BP, Schmitz TL, Peters DA, Stepan G, Insperger T (2002) Effects of radial immersion and cutting direction on chatter instability in end-milling. ASME 2002 International Mechanical Engineering Congress and Exposition:351–363Google Scholar
  22. 22.
    Insperger T, Stépán G (2004) Updated semi-discretization method for periodic delay-differential equations with discrete delay. Int J Numer Meth Eng 61:117–141MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Li KN, Darby AP (2009) A high precision direct integration scheme for nonlinear dynamic systems. J Comput Nonlin Dyn 4:1724–1732Google Scholar
  24. 24.
    Budak E, Altintaş Y, Armarego EJA (1996) Prediction of milling force coefficients from orthogonal cutting data. J Manuf Sci Eng 118(2):216–224CrossRefGoogle Scholar
  25. 25.
    Ding Y, Zhu LM, Zhang XJ, Ding H (2010) A full-discretization method for prediction of milling stability. Int J Mach Tools Manuf 50:502–509CrossRefGoogle Scholar
  26. 26.
    Zhou K, Feng PF, Xu C, Zhang JF, Wu ZJ (2017) High-order full-discretization methods for milling stability prediction by interpolating the delay term of time-delayed differential equations. Int J Adv Manuf Technol 93:2201–2214CrossRefGoogle Scholar
  27. 27.
    Dai YB, Li HK, Hao BT (2018) An improved full-discretization method for chatter stability prediction. Int J Adv Manuf Technol 2:1–8Google Scholar
  28. 28.
    Yan ZH, Wang XB, Liu ZB, Wang DQ, Jiao L, Ji YJ (2017) Third-order updated full-discretization method for milling stability prediction. Int J Adv Manuf Technol 92:2299–2309CrossRefGoogle Scholar
  29. 29.
    Tang XW, Peng FY, Rong Y, Gong YH, Li YT, Jiang LL (2017) Accurate and efficient prediction of milling stability with updated full-discretization method. Int J Adv Manuf Technol 88:2357–2368CrossRefGoogle Scholar
  30. 30.
    Ji YJ, Wang XB, Liu ZB, Wang HJ, Yan ZH (2017) An updated full-discretization milling stability prediction method based on the higher-order Hermite-Newton interpolation polynomial. Int J Adv Manuf Technol 95:2227–2242CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Qile Bo
    • 1
  • Haibo Liu
    • 1
    Email author
  • Meng Lian
    • 1
  • Yongqing Wang
    • 1
  • Kuo Liu
    • 1
  1. 1.Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of EducationDalian University of TechnologyDalianChina

Personalised recommendations