Optimization of process parameters of powder mixed EDM for high carbon high chromium alloy steel (D2 steel) through GRA approach

Abstract

Purpose

The purpose of this paper is to investigate the process parameters and optimise the machining input parameter of powder mixed electric discharge machining for high carbon high chromium alloy steel (D2 steel) for the industrial application. Grey relational analysis approach has been used to obtain the multiple performance output response.

Design/methodology/approach

In this experimental work, input parameters, namely, pulse on-time, discharge current, tool material and grit size, are selected. The design of the experiment has been constructed with the help of MINITAB 7 Software, in which L16 orthogonal array has been preferred for the experimentation. The effect of input parameters, namely, material removal rate, tool wear rate and surface roughness, is investigated. Grey relational analysis and analysis of variance are performed to optimise the input parameters and better output results.

Findings

In this experimentation, there is an increment of tool wear rate by 64.49 per cent, material removal rate by 47.14 per cent and surface roughness by 35.82 per cent.

Practical implications

A lot of practical applications have been found in many different material processing industries like metallurgy, machinery, electronics, transportation, military science, agricultural machinery, etc. These practical applications have brought forward definite and noticeable economic benefits.

Originality/value

The reader is given a general overview on the machining investigation and optimisation of processes parameters through the grey theory approach. It gives a new framework to investigate the problems where multiple input machining variable and various output responses are obtained in single optimised parameters.

Citation

Singh, K.J. (2018), "Optimization of process parameters of powder mixed EDM for high carbon high chromium alloy steel (D2 steel) through GRA approach", Grey Systems: Theory and Application, Vol. 8 No. 4, pp. 388-398. https://doi.org/10.1108/GS-01-2018-0001