Abstract
This paper envisages the multi-response optimization of machining parameters in hot turning of stainless steel (type 316) based on Taguchi technique. The workpiece heated with liquid petroleum gas flame burned with oxygen was machined under different parameters, i.e., cutting speed, feed rate, depth of cut, and workpiece temperature on a conventional lathe. The effect of cutting speed, feed rate, depth of cut, and workpiece temperature on surface roughness, tool life, and metal removal rate have been optimized by conducting multi-response analysis. From the grey analysis, a grey relational grade is obtained and based on this value an optimum level of cutting parameters has been identified. Furthermore, using analysis of variance method, significant contributions of process parameters have been determined. Experimental results reveal that feed rate and cutting speed are the dominant variables on multiple performance analysis and can be further improved by the hot turning process.
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References
Kitagaea T, Maekawa K (1990) Plasma hot machining for new engineering materials. Wear 139:251–267
Chen NNS, Lo KC (1974) Factors affecting tool life in hot machining of alloy steels. Int J Mach Tool Des 14:161–173
Wang MY, Lan TS (2008) Parametric optimization of multi-objective precision turning using grey relational analysis. Inf Technol J 7(7):1072–1076
Raguram V, Muju MK (1980) Improving tool life by magnetization in hot turning machining. Int J Mach Tools Manuf 20:87–96
Tosum N, Ozler L (2002) A study of tool life in hot machining using artificial neural networks and regression analysis method. J Mater Process Technol 124:99–104
Tosum N, Ozler L (2004) Optimization for hot turning operations with multiple performance characteristics. Int J Adv Manuf Technol 23:777–782
Noorul Haq A, Marimuthu P, Jeyapaul R (2008) Multi response optimization of machining parameters of drilling Al/Sic metal matrix composite using grey relational analysis in the Taguchi method. Int J Adv Manuf Technol 37:250–255
Bhattacharyya A (2000) Metal cutting—theory and practice. New Central Book Agencies Private Limited, Calcutta
Tonshoff HK, Wobker HG, Brandt D (1996) Tool wear and surface integrity in hard turning. Prod Eng 3(1):19–24
Bundell T (1998) Taguchi methods. Proceeding of the 1998 European Conference on Taguchi Methods, Elsevier
Aravindan S, Naveen Sait A, Noorul Haq A (2008) A machinablity study of GFRP pipes using statistical techniques. Int J Adv Manuf Technol 37:1069–1081
Deng J (1989) Introduction to grey system. J Grey Syst 1:1–24
Patel Pulak KM, Pandy M, Venkateswara Rao P (2010) Optimisation of process parameters for multi-performance characteristics in EDM of Al2O3 ceramic composite. Int J Adv Manuf Technol 47:1137–1147
Hsiao YF, Tarng YS, Huang WJ (2010) Optimization of plasma arc welding parameters by using the Taguchi method with the grey relational analysis. Mater Manuf Process 23(1):51–58
Ragunath N, Pandey PM (2007) Improving accuracy through shrinkage modeling by using Taguchi method in selective laser sintering. Int J Mach Tools Manuf 47:985–995
Lua HS, Changb CK, Hwanga NC, Chungc CT (2009) Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling. J Mater Process Technol 209:3808–3817
Pan LK, Wang CC, Wei SL, Sher HF (2007) Optimizing multiple quality characteristics via Taguchi method-based grey analysis. J Mater Process Technol 182:107–116
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Ranganathan, S., Senthilvelan, T. Multi-response optimization of machining parameters in hot turning using grey analysis. Int J Adv Manuf Technol 56, 455–462 (2011). https://doi.org/10.1007/s00170-011-3198-5
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DOI: https://doi.org/10.1007/s00170-011-3198-5