Abstract
This paper investigated the multi performance characteristics of wire electrical discharge machining for an optimal machining parameters to get low kerf and high material removal rate at the same time. The machining parameters i.e arc on time, on time, servo voltage and wire feed were used in this experiment. Based on L9 orthogonal array, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) was used to study the machining parameters of DIN 1.2510 tool steel. Multi response characteristics were solved by Taguchi method combined grey relational analysis. Experimental results are provided to demonstrate the effectiveness of this method i.e. kerf decreased from 354 μm to 345 μm, while material removal rate (MRR) increased from 9,313 mm3/min to 13,989 mm3/min. From the optimization result validated in the confirmation experiment the machining parameters combination that could produce the optimum responses are arc on time of 2 A, pulse on time of 8 μs, servo voltage 80 V and wire feed 60 mm/min.
Highlights
The process of wire dielectrical discharge machining is a thermo-electric non conventional machining process based on the erosion due to electric sparks to produce complex shapes, accurate and precision using brass wire electrode [1]
This paper studies wire-EDM of DIN 1.2510 steel and optimize two characteristics performance, i.e. kerf and material removal rate using Taguchi combined grey relational analysis
Wire-EDM of DIN 1.2510 is carried out input parameters considered as arc on time, on time, servo voltage, and wire feed, and the response parameters as kerf and material removal rate (MRR)
Summary
The process of wire dielectrical discharge machining is a thermo-electric non conventional machining process based on the erosion due to electric sparks to produce complex shapes, accurate and precision using brass wire electrode [1]. In wire-EDM, kerf (gap of width) and material removal rate (MRR) is two of the most significant performance. The material removal rate (MRR), surface roughness and kerf in wire-EDM of D2 tool steel using Taguchi’s L18 orthogonal array was analyzed by Ikram et al [11]. Deng [12] established the theory systems of grey in 1982 It helps to solve complexed interrelationship among multi objective performance characteristics successfully. Balasubramanian et al [13] optimized surface roughness and material removal rate width using Taguchi method and grey relational grade with Taguchi’s L8 orthogonal array. This paper studies wire-EDM of DIN 1.2510 steel and optimize two characteristics performance, i.e. kerf and material removal rate using Taguchi combined grey relational analysis. The characteristic quality of kerf is smaller the better and material removal rate is having higher the better
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