Optimizing Finishing process in WEDMing of Titanium Alloy (Ti6Al4V) by Zinc Coated Brass Wire based on Response Surface Methodology

Danial Ghodsiyeh; Abolfazl Golshan; Navid Hosseininezhad; Mohammadhassan Hashemzadeh and   Sina Ghodsiyeh

doi:10.17485/ijst/2012/v5i10.1

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Optimizing Finishing process in WEDMing of Titanium Alloy (Ti6Al4V) by Zinc Coated Brass Wire based on Response Surface Methodology

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2012/v5i10.1

Year: 2012, Volume: 5, Issue: 10, Pages: 1-13

Original Article

Optimizing Finishing process in WEDMing of Titanium Alloy (Ti6Al4V) by Zinc Coated Brass Wire based on Response Surface Methodology

¹ Danial Ghodsiyeh^* , ² Abolfazl Golshan, ³ Navid Hosseininezhad, ⁴Mohammadhassan Hashemzadeh and ⁵ Sina Ghodsiyeh

^{1, 3, 4}Faculty of Mechanical Engineering,
2 Faculty of Mechanical Engineering, Universiti Putra Malaysia, 43300,
⁵ Department of Mechanical, Islamic Azad University, Khomeini shahr Branch, Isfahan, Iran [email protected]*
*Author For Correspondence
Danial Ghodsiyeh
Faculty of Mechanical Engineering
Email:[email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Determining the optimal cutting parameters has always been a critical matter to achieve high performance in different type of machining. In this study the behaviour of three control parameters base on Design of Experiment (DOE) method during WEDM of titanium alloy (Ti6Al4V) is experimentally studied. A zinc coated brass wire of 0.25mm diameter was used as tool electrode to cut the specimen. Analysis of variance (ANOVA) technique was used to find out the parameters affecting the surface roughness (SR), material removal rate (MRR) and sparking gap (SG). Assumptions of ANOVA were discussed and carefully examined using analysis of residuals. This work has been established as a second-order mathematical model based on the response surface methodology (RSM).The residual analysis and confirmation runs indicate that the proposed models could adequately describe the performance of the factors those are being investigated. The results are particularly useful for scientists and engineers to determine which subset of the process variable has the maximum influence on the process performance.