Abstract—Electrochemical machining is one of the widely used non-traditional machining processes to machine complicated shapes for electrically conducting but difficult-to-machine materials such as superalloys, Ti-alloys, alloy steel, tool steel, stainless steel, etc. Use of optimal ECM process parameters can significantly reduce the ECM operating, tooling, and maintenance cost and will produce components of higher accuracy. This paper investigates the effect and parametric optimization of process parameters for Electrochemical machining of EN-31 steel using grey relation analysis. The process parameters considered are electrolyte concentration, feed rate and applied voltage and are optimized with considerations of multiple performance characteristics including material removal rate, overcut, cylindricity error and surface roughness. Analysis of variance is performed to get contribution of each parameter on the performance characteristics and it was observed that feed rate is the significant process parameter that affects the ECM robustness. The experimental results for the optimal setting show that there is considerable improvement in the process. The application of this technique converts the multi response variable to a single response Grey relational grade and, therefore, simplifies the optimization procedure.
Index Terms—Electrochemical machining; Grey relation analysis; Material removal rate; overcut; Cylindricity error.
A. Venu Gopal is Associate Professor in the Department of Mechanical Engineering, National Institute of Technology, Warangal, India. Phone: +91-9493318537; e-mail: firstname.lastname@example.org
D. Chakradhar is Research scholar in the Department of Mechanical Enigneeing, National Institute of Technology, Warangal, India. Phone: +91-9930434229; e-mail: email@example.com
Cite: D. Chakradhar, A. Venu Gopal, "Multi-Objective Optimization of Electrochemical machining of EN31 steel by Grey Relational Analysis," International Journal of Modeling and Optimization vol. 1, no. 2, pp. 113-117, 2011.