F. Kolahan - Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
M. Azadi Moghaddam - Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
R. Golmezerji - Department of Mechanical Engineering, College of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

The present study focuses on the multi objective modeling and optimization of Surface Roughness (SR), Tool Wear Rate (TWR) and Material Removal Rate (MRR) in Electrical Discharge Machining (EDM) of 40CrMnMoS86 hot worked steel parts. The proposed approach is based on Grey Relational Analysis (GRA) and Genetic Algorithm (GA). The experimental data are gathered using Taguchi L36 design matrix. Experimental tests are conducted under varying peak current (I), voltage (V), pulse on time (Ton), pulse off time (Toff) and duty factor (). Grey relational analysis and regression modeling are then employed to establish the relations between machining parameters and process output responses. To find optimal parameter settings, the developed multi objective model is optimized using Genetic Algorithm. A confirmation test is also performed to verify the effectiveness of the optimization procedure in determining the optimum levels of machining parameters. The results show that the combination of Taguchi technique, Grey relational analysis and Genetic Algorithm is quite efficient in modeling and optimization EDM process parameters.

Analysis of Variance (ANOVA); Electrical Discharge Machining (EDM); Grey Relational Analysis (GRA); Genetic Algorithm (GA);Multi objective optimization