Multi-parametric Optimization of Wired Electrical Discharge Machining Process to Minimize Damage Cause in Steel - A Soft Computing based Taguchi-Grey Relation Analysis Approach

Kusumlata Jain1

Vani Agrawal2

Sayed Sayeed Ahmad3

Smaranika Mohapatra4

Prabhat Kumar Srivastava5,Email

Paramashivaiah B M6

Ritesh Bhat7,Email

1Department of Computer & Communication Engineering, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan 303007, India.
2Department of Computer Science and Applications, ITM University, Gwalior, Madhya Pradesh 474001, India.
3College of Engineering and Computing, Al Ghurair University, Dubai, UAE.
4Department of Information Technology,Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan 303007, India.
5Department of Computer Science & Engineering, Quantum University, Roorkee, Uttarakhand 247167, India.
6Department of Mechanical Engineering, Canara Engineering College, Mangaluru, Karnataka 574219, India.
7Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104 India.
 

Abstract

The automotive industry makes crucial components from a wide array of materials. EN31 steel is a highly regarded engineering functional material that meets the industry's requirements. However, conventional machining is not cost effective due to EN31's high hardness and strength. Thus, the current research focuses on the effect of wired electrical discharge machining (WEDM) process parameters on the material removal rate (MRR) and average arithmatic mean of surface roughness (Ra) of EN-31 steel, as WEDM is a highly sustainable and cost-effective alternative to the conventional machining processes. Experiments are conducted utilizing a Taguchi L27 orthogonal array with the following input parameters: servo voltage, pulse width, pulse interval, and cutting speed. Grey relational analysis (GRA) has been used to optimize the multiple responses.  The analysis of variance (ANOVA) of the grey relational grade (GRG) demonstrated that the most influential element in simultaneously improving performance measures is the speed, S (rpm) as it contributes 62.39 % to the variance in the response.

Multi-parametric Optimization of Wired Electrical Discharge Machining Process to Minimize Damage Cause in Steel - A Soft Computing based Taguchi-Grey Relation Analysis Approach