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Multi-response optimisation of machining parameters in electrical discharge machining of Al LM25/AlB2 functionally graded composite using grey relation analysis

Publication Type : Journal Article

Publisher : International Journal of Machining and Machinability of Materials

Source : International Journal of Machining and Machinability of Materials, Volume 20, Issue 3, p.193-213 (2018)

Url : https://www.inderscienceonline.com/doi/abs/10.1504/IJMMM.2018.093529

Keywords : analysis of variance, ANOVA, EDM, Electrical discharge machining, FGMs, Functionally graded materials, GRA, Grey relation analysis, multi-response optimisation, Orthogonal array

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2018

Abstract : The main objective of this paper is to optimise the tool wear rate, material removal rate and surface roughness in electrical discharge machining of aluminium diboride (AlB2) reinforced aluminium LM25 functionally graded composite. Peak current, pulse-on time and flushing pressure were the parameters considered for carrying out the experiments. The optimisation process was accomplished through grey relation analysis to obtain the minimum tool wear rate and surface roughness with maximum material removal rate. Analysis of variance was employed to determine the effect of each parameter on the responses. The results revealed that peak current, pulse-on time and flushing pressure had an impact of 43.45%, 19.45% and 12.94% respectively on the responses. The responses were also plotted against all combinations of parameters. The surface plots exposed that peak current played a major role in increasing material removal rate and surface roughness, while the increasing pulse-on time lead to a decrease in tool wear rate.

Cite this Research Publication : Dr. Radhika N, Punnath, N., and Katamreddy, S. Charan, “Multi-response optimisation of machining parameters in electrical discharge machining of Al LM25/AlB2 functionally graded composite using grey relation analysis”, International Journal of Machining and Machinability of Materials, vol. 20, no. 3, pp. 193-213, 2018.

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