An experimental investigation and optimisation of performance characteristics in EDM of EN-24 alloy steel using Taguchi Method and Grey Relational Analysis

• Published in: Materials today : proceedings Vol. 4; no. 8; pp. 7438 - 7447
• Main Authors: Mishra, B.P., Routara, B.C.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2017
• Subjects: Electrical discharge machining (EDM); EN-24 alloy steel; Grey Relational Analysis; Material removal rate (MRR); Taguchi approach; Tool wear rate (TWR); EN-24 alloy steel; Taguchi approach; Electrical discharge machining (EDM); Material removal rate (MRR); Tool wear rate (TWR); Grey Relational Analysis
• ISSN: 2214-7853; 2214-7853
• DOI: 10.1016/j.matpr.2017.07.075

This investigation addresses exploration of electrical discharge machining (EDM) process on EN-24 alloy steel using Taguchi robust design approach and multi Objective Grey Relational Grade with four controllable input parameters such as Pulse on time (TON), Pulse off time (Toff), Peak current (I P) and Flushing pressure (Fp)for analysis of Material removal rate (MRR) and Tool wear rate (TWR).The design matrix for experimentation with different treatment conditions are chosen utilising L9 orthogonal array. From detailed study, it is found that different combinations of EDM process parameters are necessary to achieve enhanced MRR and reduced TWR for EN-24 alloy steel. The objective function S/N (Signal to Noise) ratio and analysis of variance (ANOVA) are used to analyse the predominant effect of the input parameters on MRR and TWR as well as to establish the optimum setting level of control factors with significant contribution of input controllable parameters on output responses. In this study, single objective optimization is established by Taguchi methodology and optimal factor settings for multi objective optimization of two output responses MRR and TWR collectively are identified using Grey relational analysis. Significant contribution of input controllable parameters on output response MRR is also identified statistically.The findings from this study will be very useful for process engineers to formulate computer aided process planning (CAPP) and manufacturing engineers to select optimum level of EDM process parameters to machine EN-24 alloy steel to minimise the loss function in the process contributing to minimum lead time with cost