Advertisement

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

  • Boling Yan
  • Lida Zhu
ORIGINAL ARTICLE
  • 42 Downloads

Abstract

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.

Keywords

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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

Copyright information

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

Authors and Affiliations

  1. 1.Northeastern UniversityShenyangChina

Personalised recommendations