Research on milling stability of thin-walled parts based on improved multi-frequency solution

  • Boling Yan
  • Lida ZhuEmail author


Chatter occurs more frequently due to the lower stiffness of the thin-walled parts, which may exert damaging effect on the machined surface of workpiece. To avoid chatter and predict the stable zone more precisely, a relative transfer function was introduced to consider dynamic properties of both milling tool and workpiece, and an improved multi-frequency solution was employed to predict the critical cutting depth in axial direction. Verified by a cutting test and time domain simulation, improved multi-frequency solution had been proven to be more accurate than zero-order analysis. The proposal of improved multi-frequency solution is important for the chatter suppression techniques to improve the processing efficiency and quality in the aerospace industry.


Chatter Multi-frequency solution Thin-walled parts Relative transfer function 


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  1. 1.
    Long XH, Balachandran B, Mann BP Dynamics of milling processes with variable time delays. Nonlinear Dyn 2007, 47(1–3):49–63Google Scholar
  2. 2.
    Altintaş Y, Budak E (1995) Analytical prediction of stability lobes in milling. Cirp 44(1):357–362CrossRefGoogle Scholar
  3. 3.
    Bayly PV, Mann BP, Schmitz TL, Peters DA, Stepan G et al (2015) Effects of radial immersion and cutting direction on chatter instability in end-milling. ASME Int Mech Eng Congress Exposition:351–363Google Scholar
  4. 4.
    Merdol SD, Altintas Y (2002) Mechanics and dynamics of serrated end mills. ASME Int Mech Eng Congress Exposition:337–342Google Scholar
  5. 5.
    Merdol SD, Altintas Y (2004) Multi frequency solution of chatter stability for low immersion milling. J Manuf Sci Eng 126(3):459–466CrossRefGoogle Scholar
  6. 6.
    Altintas Y, Stepan G, Merdol SD, Dombovari Z (2009) Chatter stability of milling in frequency and discrete time domain. Cirp J Manuf Sci Technol 1(1):35–44CrossRefGoogle Scholar
  7. 7.
    Zatarain M, Bediaga I, Muñoa J (2010) Analysis of directional factors in milling: importance of multi-frequency calculation and of the inclusion of the effect of the helix angle. Int J Adv Manuf Technol 47(5–8):535–542CrossRefGoogle Scholar
  8. 8.
    Li ZQ, Liu Q, Ming XZ, Wang X, Dong YF (2014) Cutting force prediction and analytical solution of regenerative chatter stability for helical milling operation. Int J Adv Manuf Technol 73(1–4):433–442CrossRefGoogle Scholar
  9. 9.
    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
  10. 10.
    Tang XW, Peng FY, Yan R, Gong YH, Li X (2016) An effective time domain model for milling stability prediction simultaneously considering multiple modes and cross-frequency response function effect. Int J Adv Manuf Technol 86(1–4):1037–1054CrossRefGoogle Scholar
  11. 11.
    Eynian M (2015) Vibration frequencies in stable and unstable milling. Int J Mach Tool Manu 90:44–49CrossRefGoogle Scholar
  12. 12.
    Zhu LD, Liu BG, Chen HY (2018) Research on chatter stability in milling and parameter optimization based on process damping. J Vib Control 24(12):2642–2655CrossRefGoogle Scholar
  13. 13.
    Ding Y, Zhu LD (2018) Investigation on chatter stability of thin-walled parts considering its flexibility based on finite element analysis. Int J Adv Manuf Technol 94(9–12):3173–3187CrossRefGoogle Scholar
  14. 14.
    Li ZQ, Wang ZK, Shi XF (2017) Fast prediction of chatter stability lobe diagram for milling process using frequency response function or modal parameters. Int J Adv Manuf Technol 89(9–12):1–10Google Scholar
  15. 15.
    Rusinek R, Zaleski K (2016) Dynamics of thin-walled element milling expressed by recurrence analysis. Meccanica 51(6):1275–1286CrossRefGoogle Scholar
  16. 16.
    Wan M, Dang XB, Zhang WH, Yang Y (2018) Optimization and improvement of stable processing condition by attaching additional masses for milling of thin-walled workpiece. Mech Syst Signal Process 103:196–215CrossRefGoogle Scholar
  17. 17.
    Feng J, Wan M, Gao TQ, Zhang WH (2018) Mechanism of process damping in milling of thin-walled workpiece. Int J Mach Tool Manu 134:1–19CrossRefGoogle Scholar
  18. 18.
    Wan M, Gao TQ, Feng J, Zhang WH (2019) On improving chatter stability of thin-wall milling by prestressing. J Mater Process Technol 264:32–44CrossRefGoogle Scholar
  19. 19.
    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 Tool Manu 109:36–48CrossRefGoogle Scholar
  20. 20.
    Totis G (2017) Breakthrough of regenerative chatter modeling in milling by including unexpected effects arising from tooling system deflection. Int J Adv Manuf Technol 89(9–12):2515–2534CrossRefGoogle Scholar
  21. 21.
    Zhang YB, Li CH, Ji HJ, Yang XH et al (2017) Analysis of grinding mechanics and improved predictive force model based on material-removal and plastic-stacking mechanisms. Int J Mach Tool Manu 122:81–97CrossRefGoogle Scholar
  22. 22.
    Yang M, Li CH, Zhang YB, Jia DZ et al (2017) Maximum undeformed equivalent chip thickness for ductile-brittle transition of zirconia ceramics under different lubrication conditions. Int J Mach Tool Manu 122:55–65CrossRefGoogle Scholar
  23. 23.
    Liu CF, Zhu LD, Ni CB (2018) Chatter detection in milling process based on VMD and energy entropy. Mech Syst Signal Process 105:169–182CrossRefGoogle Scholar

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© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Northeastern UniversityShenyangChina

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