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Research on the matching relationship between ultrasonic-assisted grinding parameters and workpiece surface roughness

  • Siyuan Sun
  • Jinyuan Tang
  • Wen ShaoEmail author
  • Changshun Chen
  • Yaoxi Liu
ORIGINAL ARTICLE
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Abstract

As a nontraditional type of processing technology, ultrasonic-assisted grinding (UAG) can effectively improve the surface integrity. A considerable research effort has been devoted to investigate the impact of various processing parameters on surface roughness. However, few studies have been conducted on the effects of matching relationship between different parameters. In this study, the numerical model of a dressed grinding wheel is constructed using a measured diamond pen. Based on the grinding kinematics, the micro surface topography of the workpiece is generated. The relationship between surface roughness and three main processing parameters is studied, and the concept of critical ultrasonic amplitude is proposed. It is found that the ultrasonic grinding can effectively weaken the deterioration of the roughness by increasing the depth of cut, and then, the relationship between the critical ultrasonic amplitude and the depth of cut is obtained. Furthermore, the coupling relation is explained from the angle of a single abrasive grain. Finally, the accuracy of the findings is verified by the experimental results, which may serve as an effective method or reference for the setting of ultrasonic grinding parameters.

Keywords

Ultrasonic-assisted grinding Processing parameters Matching relationship Critical ultrasonic amplitude 

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Notes

Funding information

This study received financial supports from the National Key R&D Program of China through Grant No. 2017YFB1300700; the National Natural Science Foundation of China (NSFC) through Grant Nos. 51535012, 51705542, and U1604255; and Key Research and Development Project of Hunan Province through Grant No. 2016JC2001.

References

  1. 1.
    Shao W, Li XS, Sun Y, Huang H, Tang JY (2018) An experimental study of temperature at the tip of point-attack pick during rock cutting process. Int J Rock Mech Min Sci 107:39–47CrossRefGoogle Scholar
  2. 2.
    Shao W, Li XS, Sun Y, Huang H (2017) Parametric study of rock cutting with SMART*CUT picks. Tunnel Undergr Space Technol 61:134–144CrossRefGoogle Scholar
  3. 3.
    Qi H, Xie Z, Hong T, Wang YY, Kong FZ, Wen DH (2017) CFD modelling of a novel hydrodynamic suspension polishing process for ultra-smooth surface with low residual stress. Powder Technol 317:320–328CrossRefGoogle Scholar
  4. 4.
    Qi H, Wen DH, Lu CD, Li G (2016) Numerical and experimental study on ultrasonic vibration-assisted micro-channelling of glasses using an abrasive slurry jet. Int J Mech Sci 110:94–107CrossRefGoogle Scholar
  5. 5.
    Long YY, Li YL, Sun J, Ille I, Li JF, Twiefel J (2018) Effects of process parameters on force reduction and temperature variation during ultrasonic assisted incremental sheet forming process. Int J Adv Manuf Technol 97:13–24CrossRefGoogle Scholar
  6. 6.
    Li DG, Tang JY, Chen HF, Shao W (2018) Study on grinding force model in ultrasonic vibration-assisted grinding of alloy structural steel. Int J Adv Manuf Technol.  https://doi.org/10.1007/s00170-018-2929-2
  7. 7.
    Liao DR, Shao W, Tang JY, Li JP, Tao X (2018) Numerical generation of grinding wheel surfaces based on time series method. Int J Adv Manuf Technol 94:561–569CrossRefGoogle Scholar
  8. 8.
    Liao DR, Shao W, Tang JY, Li JP (2018) An improved rough surface modeling method based on linear transformation technique. Tribol Int 119:786–794CrossRefGoogle Scholar
  9. 9.
    Zhou WH, Tang JY, Chen HF, Shao W, Zhao B (2019) Modeling of tooth surface topography in continuous generating grinding based on measured topography of grinding worm. Mech Mach Theory 131:189–203CrossRefGoogle Scholar
  10. 10.
    Zhou WH, Tang JY, Chen HF, Zhu CC, Shao W (2018) Modeling of tooth surface topography in continuous generating grinding based on measured topography of grinding worm. Int J Mech Sci 144:639–653CrossRefGoogle Scholar
  11. 11.
    Tawakoli T, Azarhoushang B (2009) Effects of ultrasonic assisted grinding on CBN grinding wheels performance. ASME Int Manuf Sci Eng Conf 2:209–214Google Scholar
  12. 12.
    Tawakoli T, Azarhoushang B (2008) Influence of ultrasonic vibrations on dry grinding of soft steel. Int J Mach Tools Manuf 48(14):1585–1591CrossRefGoogle Scholar
  13. 13.
    Nik MG, Movahhedy MR, Akbari J (2012) Ultrasonic-assisted grinding of Ti6Al4 V alloy. Procedia CIRP 1:353–358CrossRefGoogle Scholar
  14. 14.
    Chen HF, Tang JY, Shao W, Zhao B (2018) An investigation on surface functional parameters in ultrasonic-assisted grinding of soft steel. Int J Adv Manuf Technol 97:2697–2702CrossRefGoogle Scholar
  15. 15.
    Chen HF, Tang JY, Shao W, Zhao B (2018) An investigation of surface roughness in ultrasonic assisted dry grinding of 12Cr2Ni4A with large diameter grinding wheel. Int J Precis Eng Manuf 19(6):929–936CrossRefGoogle Scholar
  16. 16.
    Wang Y, Lin B, Wang S, Cao X (2014) Study on the system matching of ultrasonic vibration assisted grinding for hard and brittle materials processing. Int J Mach Tools Manuf 77:66–73CrossRefGoogle Scholar
  17. 17.
    Wang Y, Lin B, Cao X, Wang S (2014) An experimental investigation of system matching in ultrasonic vibration assisted grinding for titanium. J Mater Process Technol 214(9):1871–1878CrossRefGoogle Scholar
  18. 18.
    Chen HF, Tang JY, Lang XJ, Huang YL, He YH (2014) Influences of dressing lead on surface roughness of ultrasonic-assisted grinding. Int J Adv Manuf Technol 71(9–12):2011–2015CrossRefGoogle Scholar
  19. 19.
    Ding H, Tang JY, Shao W, Zhou YS, Wan GX (2017) Optimal modification of tooth flank form error considering measurement and compensation of cutter geometric errors for spiral bevel and hypoid gears. Mech Mach Theory 118:14–31CrossRefGoogle Scholar
  20. 20.
    Shao W, Ding H, Tang JY, Peng SD (2018) A data-driven optimization model to collaborative manufacturing system considering geometric and physical performances for hypoid gear product. Robot Comput Integr Manuf 54:1–16CrossRefGoogle Scholar
  21. 21.
    Shao W, Ding H, Tang JY, Peng SD (2018) Data-driven operation and compensation approaches to tooth flank form error measurement for spiral bevel and hypoid gears. Measurement 122:347–357CrossRefGoogle Scholar
  22. 22.
    Ding H, Tang JY, Shao W, Peng SD (2018) An innovative determination approach to tooth compliance for spiral bevel and hypoid gears by using double-curved shell model and Rayleigh–Ritz approach. Mech Mach Theory 130:27–46CrossRefGoogle Scholar
  23. 23.
    Jiang JL, Ge PQ, Bi WB, Zhang L, Wang DX, Zhang Y (2013) 2D/3D ground surface topography modeling considering dressing and wear effects in grinding process. Int J Mach Tools Manuf 74:29–40CrossRefGoogle Scholar
  24. 24.
    Saad A, Bauer R, Warkentin A (2010) Investigation of single-point dressing overlap ratio and diamond-roll dressing interference angle on surface roughness in grinding. Trans Can Soc Mech Eng 34(2):295–308CrossRefGoogle Scholar
  25. 25.
    Oliveira JFG, Bottene AC, Franca TV (2010) A novel dressing technique for texturing of ground surfaces. Ann CIRP 59(1):361–364CrossRefGoogle Scholar
  26. 26.
    Malkin S (1989) Grinding technology: theory and applications of machining with abrasives, 1st edn. Ellis Horwood, New YorkGoogle Scholar
  27. 27.
    Zhou X, Xi F (2002) Modeling and predicting surface roughness of the grinding process. Int J Mach Tools Manuf 42(8):969–977CrossRefGoogle Scholar
  28. 28.
    Malkin S (2008) Grinding technology: theory and applications of machining with abrasives, 2nd edn. Industrial Press Inc.Google Scholar

Copyright information

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

Authors and Affiliations

  • Siyuan Sun
    • 1
  • Jinyuan Tang
    • 1
  • Wen Shao
    • 1
    Email author
  • Changshun Chen
    • 1
  • Yaoxi Liu
    • 1
  1. 1.State Key Laboratory of High Performance Complex Manufacturing, School of Mechanical and Electrical EngineeringCentral South UniversityChangshaChina

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