Statistical multi-objective optimization of electrical discharge machining parameters in machining titanium grade 5 alloy using graphite electrode

Author:

Sivam Saravanan P12,Michaelraj Antony L2,Kumar S Satish3,Prabhakaran G4,Dinakaran D5,Ilankumaran V1

Affiliation:

1. Engineering Department, Nizwa College of Technology, Nizwa, Sultanate of Oman

2. Department of Mechanical Engineering, SRM University, Tamilnadu, India

3. Department of Production Engineering, Velammal Engineering College, Tamilnadu, India

4. Department of Mechanical Engineering, Velammal Engineering College, Tamilnadu, India

5. Department of Mechanical Engineering, Hindustan University, Tamilnadu, India

Abstract

In industrial applications, particularly in aero, marine and medical industries, titanium has received great attention as a useful material and electrical discharge machining as its machining process. Selection of optimal machining parameters in a multi-objective environment is essential for specific workpiece and tool material combination, which is the concern of industries to improve the overall productivity at less cost. In this article, optimization of critical electrical discharge machining parameters such as pulse current, on time of pulse, off time of pulse and tool geometry depending on the responses such as titanium machining rate, graphite wear rate, surface roughness and deviation between entry and exit while machining titanium grade 5 alloy with graphite tool electrode at negative polarity is presented. Taguchi’s L27 orthogonal array was used to design the experiment with interaction between factors. The weighing method was used to integrate different objectives into one performance. The optimal combination of process parameters was found statistically using signal-to-noise ratios. Significance was checked by analysis of variance. Optimum parameters were found to be pulse current 15 A, on time of pulse 50 µs, off time of pulse 200 µs and cylindrical tool geometry. Resultant percentage improvements in different responses were presented.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference17 articles.

1. Lutjering G, Williams JC. Titanium: engineering materials and processes. London: Springer, 2007, pp.356–360.

2. Modelling of micro-electrodischarge machining during machining of titanium alloy Ti—6Al—4V using response surface methodology and artificial neural network algorithm

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