Advertisement

Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology

  • H. Aouici
  • H. Bouchelaghem
  • M. A. Yallese
  • M. Elbah
  • B. Fnides
ORIGINAL ARTICLE

Abstract

The hard turning process has been attracting interest in different industrial sectors for finishing operations of hard materials. In this paper, the effects of cutting speed, feed rate, and depth of cut on surface roughness, cutting force, specific cutting force, and power in the hard turning were experimentally investigated. An experimental investigation was carried out using ceramic cutting tools, composed approximately with (70 %) of Al2O3 and (30 %) of TiC, in surface finish operations on cold work tool steel AISI D3 heat-treated to a hardness of 60 HRC. Based on 33 full factorial designs, a total of 27 tests were carried out. The range of each parameter is set at three different levels, namely, low, medium, and high. Analysis of variance is used to check the validity of the model. Experimental observations show that higher cutting forces are required for machining harder work material. This cutting force gets affected mostly by feed rate followed by depth of cut. Feed rate is the most influencing factor on surface roughness. Feed rate followed by depth of cut become the most influencing factors on power; especially in case of harder workpiece. Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach. It was found that, the use of lower depth of cut value, higher cutting speed, and by limiting the feed rate to 0.12 and 0.13 mm/rev, while hard turning of AISI D3 hardened steel, respectively, ensures minimum cutting forces and better surface roughness. Higher values of depth of cut are necessary to minimize the specific cutting force.

Keywords

Hard turning AISI D3 steel Ceramic ANOVA RSM 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lawani DI, Mehta NK, Jain PK (2009) Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel. J Mater Process Technol 209:1092–1104CrossRefGoogle Scholar
  2. 2.
    Suresh R, Basavarajappa S, Samuel GL (2012) Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool. Measurement 45(7):1872–1884CrossRefGoogle Scholar
  3. 3.
    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):109–123CrossRefGoogle Scholar
  4. 4.
    Azizi MW, Belbah A, Yallese MA, Mabrouki T, Rigal JF (2012) Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel. J Mech Sci Technol 25(12):4105–4114CrossRefGoogle Scholar
  5. 5.
    Hessainia Z, Yallese MA, Chaoui K, Mabrouki T, Rigal JF (2013) On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations. Measurement 46(5):1671–1681CrossRefGoogle Scholar
  6. 6.
    Dilbag SP, Venkateswara RA (2007) Surface roughness prediction model for hard turning process. J Adv Manuf Technol 32:1115–1124CrossRefGoogle Scholar
  7. 7.
    El-Wardany TI, Kishawy HA, Elsbestawi MA (2000) Surface integrity of die material in high-speed hard machining. Part 1. Micro hardness various and residual stresses. J Manuf Eng 4(122):632–641CrossRefGoogle Scholar
  8. 8.
    Aouici H, Yallese MA, Findes B, Chaoui K, Mabrouki T (2011) Modeling and optimization of hard turning of X38CrMoV5-1 steel with CBN tool: machining parameters effects on flank wear and surface roughness. J Mech Sci Technol 25(11):2843–2851CrossRefGoogle Scholar
  9. 9.
    Bouacha K, Yallese MA, Mabrouki T, Rigal JF (2010) Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool. J Refract Met Hard Mater 28:349–361CrossRefGoogle Scholar
  10. 10.
    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 45:344–353CrossRefGoogle Scholar
  11. 11.
    Kirby ED, Zhang Z, Chen JC (2004) Development of an accelerometer based surface roughness prediction system in turning operation using multiple regression techniques. J Ind Technol 4(20):1–8Google Scholar
  12. 12.
    Doniavi A, Eskanderzade M, Tahmsebian M (2007) Empirical modeling of surface roughness in turning process of 1060 steel using factorial design methodology. J Appl Sci 7(17):2509–2513CrossRefGoogle Scholar
  13. 13.
    Al-Ahmari AM (2007) Predictive machinability models for a selected hard material in turning operations. J Mater Process Technol 190:305–311CrossRefGoogle Scholar
  14. 14.
    Horng JT, Liu NM, Chiang KT (2008) Investigating the machinability of Hadfield steel in hard turning with Al2O3/TiC mixed ceramic tool based on response surface methodology. J Mater Process Technol 208:532–541CrossRefGoogle Scholar
  15. 15.
    Kribes N, Hessainia Z, Yallese MA, Ouelaa N (2012) Statistical analysis of surface roughness by design experiments in hard turning. Mechanika 18(5):605–611Google Scholar
  16. 16.
    Neseli S, Yaldız S, Türkes E (2011) Optimization of tool geometry parameters for turning based on the response surface methodology. Measurement 44:580–587CrossRefGoogle Scholar
  17. 17.
    Gaitonde VN, Karnik SR, Figueira L, Davim JP (2009) Analysis of machinability during hard turning of cold work tool steel (type: AISI D2). Mater Manuf Process Taylor Francis 24(12):1373–1382CrossRefGoogle Scholar
  18. 18.
    Davim JP, Figueira L (2007) Comparative evaluation of conventional and wiper ceramic tools on cutting forces, surface roughness, and tool wear in hard turning AISI D2 steel. J Eng Manuf 221:625–633CrossRefGoogle Scholar
  19. 19.
    Davim JP, Figueira L (2007) Machinability evaluation in hard turning of cold work tool steel (D2) with ceramic tools using statistical techniques. Mater Des 28:1186–1191CrossRefGoogle Scholar
  20. 20.
    Quiza R, Figueira L, Davim JP (2008) Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel. J Adv Manuf Technol 37(7–8):641–648CrossRefGoogle Scholar
  21. 21.
    Fnides B, Boutabba S, Fnides M, Aouici H, Yallese MA (2013) Cutting tools flank wear and productivity investigation in straight turning of X38CrMoV5-1 (50 HRC). J App Eng Technol 3(1):1–10CrossRefGoogle Scholar
  22. 22.
    Yallese MA, Chaoui K, Zeghib N, Boulanouar L (2009) Hard machining of hardened bearing steel using cubic boron nitride tool. J Mater Process Technol 209:1092–1104CrossRefGoogle Scholar
  23. 23.
    Gaitonde VN, Karnik SR, Faustino M, Davim JP (2009) Machinability analysis in turning tungsten-copper composite for application in EDM electrodes. J Refract Met Hard Mater 27:754–763CrossRefGoogle Scholar
  24. 24.
    Chiang KT (2008) Modeling and analysis of effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic. J Adv Manuf Technol 37:523–533CrossRefGoogle Scholar
  25. 25.
    Aouici H, Yallese MA, Fnides B, Mabrouki T (2010) Machinability investigation in hard turning of AISI H11 hot work steel with CBN tool. Mechanika 6(86):71–77Google Scholar
  26. 26.
    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 Res Devel 4:115–125CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • H. Aouici
    • 1
    • 2
  • H. Bouchelaghem
    • 1
  • M. A. Yallese
    • 1
  • M. Elbah
    • 1
  • B. Fnides
    • 3
  1. 1.Laboratoire Mécanique et Structures (LMS), Département de Génie Mécanique, FSTUniversité 08 Mai 1945GuelmaAlgeria
  2. 2.ENST-ex CT Siège DG. SNVIRouibaAlgeria
  3. 3.Département de Construction Mécanique et Productique, FGM&GPUSTHBAlgerAlgeria

Personalised recommendations