Skip to main content
Log in

Empirical models for cutting forces in finish dry hard turning of hardened tool steel at different hardness levels

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In this research, the exponential and quadratic polynomial empirical models for three-component cutting forces by employing five factors, such as the cutting speed, depth of cut, feed, workpiece hardness, and nose radius, were developed by utilizing the orthogonal regression methodology (ORM) and response surface methodology (RSM). On the other hand, an attempt has been made to experimentally investigate the effects of those factors on three-component cutting forces in finish dry hard turning (FDHT) of tool steel AISI D2 with the PCBN tool. In this investigation, based on five-factor three-level orthogonal experiments, three-component cutting forces were measured, and then, analysis of variance (ANOVA) was performed to estimate the significance of developed models and analyze the main and interaction effects of the factors. The experimental results indicated that the RSM quadratic polynomial empirical model (RSMQPEM) is much more accurate and credible than the ORM exponential empirical model (ORMEM) in predicting the three-component cutting forces. It was also found that the cutting speed and feed are the two dominant factors affecting the main cutting forces F Z; the feed is the one dominant factor affecting radial cutting force F Y and the feed cutting force F X. Additionally, the optimum cutting parameters for the hardened materials with 51, 55, 60, and 64 HRC was found.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Gaitonde VN, Karnik SR, Figueira L, Paulo Davim J (2009) Analysis of machinability during hard turning of cold work tool steel (type: AISI D2). Mater Manuf Process 24(12):1373–1382

    Article  Google Scholar 

  2. Klocke F, Brinksmeier E, Weinert K (2005) Capability profile of hard cutting and grinding processes. Ann CIRP 54(2):552–580

    Article  Google Scholar 

  3. Ranganathan S, Senthilvelan T (2009) Behavior of machining parameters in hard turning of 316 stainless steel. Int J Manuf Sci Prod 10(2):137–145

    Google Scholar 

  4. Tang L, Huang J, Xie L (2011) Finite element modeling and simulation in dry hard orthogonal cutting AISI D2 tool steel with CBN cutting tool. Int J Adv Manuf Technol 53(1/2):1167–1181

    Article  Google Scholar 

  5. Tang L, Gao C, Huang J, Lin X, Zhang J (2014) Experimental investigation of the three-component forces in finish dry hard turning of hardened tool steel at different hardness levels. Int J Adv Manuf Technol 70(9–12):1721–1729

    Article  Google Scholar 

  6. More WC, Jiang W, Brown WD, Malshe AP (2006) Tool wear and machining performance of cBN-TiN coated carbide inserts and PCBN compact inserts in turning AISI4340 hardened steel. J Mater Process Technol 180(1–3):253–262

    Article  Google Scholar 

  7. Sharma VS, Dhiman S, Sehgal R, Sharme SK (2008) Estimation of cutting forces and surface roughness for hard turning using neural networks. J Intell Manuf 19(4):473–483

    Article  Google Scholar 

  8. Sieben B, Wagner T, Biermann D (2010) Empirical modeling of hard turning of AISI 6150 steel using design and analysis of computer experiments. Prod Eng 4(2):115–125

    Article  Google Scholar 

  9. Ding T, Zhang S, Wang Y, Zhu X (2010) Empirical models and optimal cutting parameters for cutting forces and surface roughness in hard milling of AISI H13 steel. Int J Adv Manuf Technol 51(1):45–55

    Article  Google Scholar 

  10. Gopalsamy B, Mondal B, Ghosh S (2009) Optimisation of machining parameters for hard machining: grey relational theory approach and ANOVA. Int J Adv Manuf Technol 45(11–12):1068–1086

    Article  Google Scholar 

  11. Fnides B, Yallese MA, Mabrouki T, Rigal JF (2011) Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot work tool steel. Sadhana 36(1):109–123

    Article  Google Scholar 

  12. Aouici H, Yallese MA, Chaoui K, Mabrouki T, Rigal JF (2012) Analysis of surface roughness and cutting force components in hard turning with CBN tool: prediction model and cutting conditions optimization. Measurement 45(3):344–353

    Article  Google Scholar 

  13. Zhou AQ, Deng FY (2001) Experimental study on the heat treatment process for Cr12MoV steel. Die Mould Ind 000:55–57

    Google Scholar 

  14. Wang LJ, Miao B, Meng XX (2005) Analysis on the hardness and metallographic structure of Cr12MoV Steel under different heat treatment. Die Mould Ind 000:2–56

    Google Scholar 

  15. Dogra M, Sharma VS, Sachdeva A, Suri NM, Dureja JS (2010) Tool wear, chip formation and workpiece surface issues in CBN hard turning: a review. Int J Precis Eng Manuf 11(2):341–358

    Article  Google Scholar 

  16. Wen D (2002) The mechanism and technology of hard turning with PCBN tool. Dalian University of Technology, Dissertation

    Google Scholar 

  17. Liu Z, Wan Y, Zhou J (2006) Tool materials for high speed machining and their fabrication technologies. Mater Mech Eng 30(5):1–4

    Google Scholar 

  18. Kilickap E, Huseyinoglu M, Yardimeden A (2011) Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 52(1–4):79–88

    Article  Google Scholar 

  19. Natarajan U, Periyanan P, Yang S (2011) Multiple-response optimization for micro-endmilling process using response surface methodology. Int J Adv Manuf Technol 56(1–4):177–185

    Article  Google Scholar 

  20. Tang Z (1997) Fundamental of mechanical manufacture. 1st edn. Machinery Industry Press, Beijing, p 11–12

  21. Yuan Z, Song S (2009) Multivariate statistical analysis, 1st edn. 102, Beijing, pp 102–116

    Google Scholar 

  22. Fang K, Quan H (1988) Applied regression analysis, 1st edn. Science Press, Beijing, pp 202–206

    Google Scholar 

  23. Ren L (2009) Regression design and optimization, 1st edn. Science Press, Beijing, pp 232–256

    Google Scholar 

  24. Chen C, Chiang K (2011) Analyzing the design of vibration reduction with the rubber-layered laminates in the precision turning with a diamond cutting tool. Int J Adv Manuf Technol 19(1–4):101–116

    Article  Google Scholar 

  25. Li X, Yin X (2008) SPSS economic and statistical analysis, 1st edn. China Statistics Press, Beijing, pp 261–289

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Linhu Tang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, L., Cheng, Z., Huang, J. et al. Empirical models for cutting forces in finish dry hard turning of hardened tool steel at different hardness levels. Int J Adv Manuf Technol 76, 691–703 (2015). https://doi.org/10.1007/s00170-014-6291-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-014-6291-8

Keywords

Navigation