Optimization of process parameters through GRA, TOPSIS and RSA models

Nipanikar, S.; Sargade, V.; Guttedar, R.

Abstract: This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial) in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min), feed (0.08, 0.15, 0.2 mm/rev) and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oil.

How to cite this paper

        APA: Nipanikar, S., Sargade, V & Guttedar, R. (2018). Optimization of process parameters through GRA, TOPSIS and RSA models. International Journal of Industrial Engineering Computations, 9(1), 137-154.
    

        Chicago/Turabian: Nipanikar, S., Sargade, V & Guttedar, R. 2018. "Optimization of process parameters through GRA, TOPSIS and RSA models." International Journal of Industrial Engineering Computations 9, no. 1 (2018): 137-154.
    

        AMA: Nipanikar, S., Sargade, V & Guttedar, R. Optimization of process parameters through GRA, TOPSIS and RSA models. International Journal of Industrial Engineering Computations. 2018;9(1):137-154.
    

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