Skip to main content
SpringerLink
Log in

Experimental Investigation of Effects of Polishing Process on Surface Residual Stress of TC4 Blade Based on Sensitivity Analysis

  • Published:
Experimental Techniques Aims and scope Submit manuscript

Abstract

The residual compressive stress on polished surfaces can significantly delay the initiation of microscopic flaws, and improve the fatigue strength of engineered components. Reasonable selection of polishing parameter ranges plays an important role in controlling residual compressive stress on finished surface, which is closely related to the service performances of aero-engine blade. In order to investigate the influence of each process parameter on residual compressive stress and obtain the optimal parameter ranges for the maximum and stable residual stress range, the sensitivity analysis method was presented in this study. The polishing experiments were designed by using four-factor three-level Central-Composite design theory for TC4 titanium alloy thin-walled blades. Based on the residual stress prediction model developed utilizing a multiple regression method, a global relative sensitivity analysis was conducted to identify the significant and insignificant parameters. Then the stable range and the instable range were divided based on sensitivity curves, and a parameter range optimization method was subsequently presented. Finally, the optimal parametric ranges for residual stress in polishing process were obtained as follows: rotation speed within [9500 r/min, 11,000 r/min], feed rate within [100 mm/min, 200 mm/min], contact force within [0.6 N, 1.8 N] and row spacing within [6 mm, 7 mm].

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Ralph B (2008) Titanium alloys: an atlas of structures and fracture features. Mater Charact 59(3):348–348

    Google Scholar 

  2. Huo WG, Xu JH, Fu YC, Su HH (2010) Dry grinding of Ti6Al4V alloy with flap wheels. Trans Nanjing U Aeronaut Astronaut 27(2):131–137

    Google Scholar 

  3. Yang ZC, Zhang DH, Yao CF (2009) Effects of high-speed milling parameters on surface integrity of TC4 titanium alloy. J Northwestern Polytechnical U 27(4):538–543

    CAS  Google Scholar 

  4. Xiao GJ, Huang Y, Yin J (2016) An integrated polishing method for compressor blade surfaces. Int J Adv Manuf Technol 88(5–8):1–11

    Google Scholar 

  5. Hossain S, Zheng G, Truman CE, Smith DJ (2017) Application of multiple analysis methods in optimising complex residual stress characterisation. Exp Tech 41(5):483–503

    Article  Google Scholar 

  6. Chen G, Yi K, Yang M, Liu W, Xu X (2014) Factor effect on material removal rate during phosphate laser glass polishing. Mater Manuf Process 29(6):721–725

    Article  CAS  Google Scholar 

  7. Vardanjani MJ, Ghayour M, Homami RM (2016) Analysis of the vibrational stress relief for reducing the residual stresses caused by machining. Exp Tech 40(2):705–713

    Article  Google Scholar 

  8. Buldum BB, Cagan SC (2017) Study of ball burnishing process on the surface roughness and microhardness of AZ91D alloy. Exp Tech 9:1–9

    Google Scholar 

  9. Wei SL, Zhao H, Jing JT, Yun FH, Li XL (2017) Investigation on surface residual stress distribution and evaluation of engineering ceramics in rotary ultrasonic grinding machining. P I Mech Eng C-J Mec 231(15):2773–2782

    Article  Google Scholar 

  10. Arrasmith SR, Jacobs SD, Lambropoulos JC, Maltsev A, Golini D, Kordonski WI (2001) Use of magnetorheological finishing (MRF) to relieve residual stress and subsurface damage on lapped semiconductor silicon wafers. Proc SPIE 4451:286–294

    Article  CAS  Google Scholar 

  11. Shao Y, Fergani O, Li B, Liang SY (2016) Residual stress modeling in minimum quantity lubrication grinding. Int J Adv Manuf Technol 83(5–8):743–751

    Article  Google Scholar 

  12. Rech J, Kermouche G, Claudin C (2008) Modelling of the residual stresses induced by belt finishing on a AISI52100 hardened steel. Int J Mater Form 1(1):567–570

    Article  Google Scholar 

  13. Vashista M, Paul S (2008) Study of the effect of process parameters in high-speed grinding on surface integrity by Barkhausen noise analysis. P I Mech Eng B-J Eng 222(12):1625–1637

    CAS  Google Scholar 

  14. 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 317:320–328

    Article  CAS  Google Scholar 

  15. Hamdi H, Zahouani H, Bergheau JM (2004) Residual stresses computation in a grinding process. J Mater Process Technol 147(3):277–285

    Article  CAS  Google Scholar 

  16. Tan L, Zhang DH, Yao CF, Wu DX, Zhang JY (2017) Evolution and empirical modeling of compressive residual stress profile after milling, polishing and shot peening for TC17 alloy. J Manuf Process 26:155–165

    Article  Google Scholar 

  17. Zhao PB, Shi YY (2013) Composite adaptive control of belt polishing force for aero-engine blade. China J Mech Eng 26(5):988–996

    Article  Google Scholar 

  18. Huai WB, Tang H, Shi Y, Lin XJ (2017) Prediction of surface roughness ratio of polishing blade of abrasive cloth wheel and optimization of processing parameters. Int J Adv Manuf Technol 90(1–4):699–708

    Article  Google Scholar 

  19. Chen Z, Shi YY, Lin XJ (2018) Evaluation and improvement of material removal rate with good surface quality in TC4 blisk blade polishing process. J Adv Mech Des Syst 12(4):1–12

    Google Scholar 

  20. Leyens C, Peters M (2003) Titanium and titanium alloys: fundamentals and applications. John Wiley & Sons

  21. Zhu Z, Guo K, Sun J, Li J, Liu Y, Chen L, Zhang Y (2018) Evolution of 3D chip morphology and phase transformation in dry drilling Ti6Al4V alloys. J Manuf Process 34:531–539

    Article  Google Scholar 

  22. Wang J (2018) The study on nanocrystallization and properties on the surface of TC 4 titanium alloy after ultrasonic impact treatment and high temperature annealing. Diss:20–21

  23. Zhang JF, Shi YY, Lin XJ, Li ZS (2017) Five-axis abrasive belt flap wheel polishing method for leading and trailing edges of aero-engine blade. Int J Adv Manuf Technol 93(9–12):3383–3393

    Article  Google Scholar 

  24. Tan L, Yao C, Zhang D, Ren J (2016) Empirical modeling of compressive residual stress profile in shot peening tc17 alloy using characteristic parameters and sinusoidal decay function. P I Mech Eng B-J Eng 232(5):855–866

    Google Scholar 

  25. Zhou J, Ren J, Yao C (2017) Multi-objective optimization of multi-axis ball-end milling Inconel 718 via grey relational analysis coupled with RBF neural network and PSO algorithm. Measurement 102:271–285

    Article  Google Scholar 

  26. Zhou J, Ren J, Tian W (2017) Grey-RBF-FA method to optimize surface integrity for inclined end milling Inconel 718. Int J Adv Manuf Technol 91(9–12):2975–2993

    Article  Google Scholar 

  27. Yoganandh J, Kannan T, Babu SK, Natarajan S (2013) Optimization of GMAW process parameters in austenitic stainless steel cladding using genetic algorithm based computational models. Exp Tech 37(5):48–58

    Article  Google Scholar 

  28. Tian RX, Yao CF, Huang XC, Ren JX, Zhang DH (2010) Process parameter interval sensitivity and optimization of machined surface roughness for high-speed milling of titanium alloys. Acta Aeronaut Et Astronaut Sinica 31(12):2464–2470

    CAS  Google Scholar 

  29. Srinivasulu GN, Subrahmanyam T, Rao VD (2011) Parametric sensitivity analysis of PEM fuel cell electro-chemical model. Int J Hydrog Energy 36(22):14838–14844

    Article  CAS  Google Scholar 

  30. Wang GS, Xia J, Chen JF (2010) A multi-parameter sensitivity and uncertainty analysis method to evaluate relative importance of parameters and model performance. Geogr Res 29(2):263–270

    Google Scholar 

  31. Nassar MA (2011) Multi-parametric sensitivity analysis of CCHE2D for channel flow simulations in Nile River. J Hydro-environ Res 5(3):187–195

    Article  Google Scholar 

  32. Qian WX, Yin XW, He XH, Xie LY (2006) Sensitivity analysis of influencing parameters on fatigue life of aeroengine compressor disk. J Northeastern U 27(6):677–680

    Google Scholar 

  33. Karthikeyan R, Balasubramanian V (2013) Statistical optimization and sensitivity analysis of friction stir spot welding process parameters for joining AA 7075 aluminum alloy. Exp Tech 37(2):6–15

    Article  Google Scholar 

  34. Fernandus MJ, Senthilkumar T, Balasubramanian V, Rajakumar S (2014) Optimizing diffusion bonding parameters to maximize the strength of AA6061 aluminum and AZ61A magnesium alloy joints. Exp Tech 38(4):21–36

    Article  Google Scholar 

  35. Yu T, Shi YY, He XD, Kang C, Deng B, Song SB (2017) Optimization of parameter ranges for composite tape winding process based on sensitivity analysis. Appl Compos Mater 24(4):821–836

    Article  Google Scholar 

Download references

Acknowledgments

This work was sponsored by the National Science and Technology Major Projects of China (2015ZX04001003) and Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (CX201946).

Author information

Authors and Affiliations

  1. The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi’an, 710072, China

    Z. Chen, Y. Shi, X. Lin, P. Zhao & C. Kang

  2. Xi’an Electronic Engineering Research Institute, Xi’an, 710100, China

    T. Yu

Authors
  1. Z. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Y. Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. X. Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. T. Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. P. Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C. Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Z. Chen.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Z., Shi, Y., Lin, X. et al. Experimental Investigation of Effects of Polishing Process on Surface Residual Stress of TC4 Blade Based on Sensitivity Analysis. Exp Tech 43, 729–738 (2019). https://doi.org/10.1007/s40799-019-00333-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40799-019-00333-z

Keywords

Search

Navigation