Optimization of Process Parameters of Surfactant and Graphite Powder Mixed Dielectric EDM through Taguchi-Grey Relational Analysis

This paper presents an optimization of process parameters of Electrical Discharge Machining (EDM) process with surfactant and graphite powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on Taguchi orthogonal array (OA) combined with Grey Relational Analysis. A grey relational grade (GRG) was calculated based on Grey Relational Analysis. A grey relational grade is used to optimize the EDM process with multiple performance characteristics. Taguchi L9 orthogonal array was used to design the experiments. The machining parameters such as peak current, surfactant concentration, and graphite powder concentration were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR). Experiments were conducted using electrolyte copper as the tool and PH17-4 stainless steel as the work piece. Results revealed that machining performance has been improved considerably using this approach. The confirmation experiments were conducted at optimum parametric setting and it was found that the predicted values of responses at optimal combination of parameters are in good agreement with the results of confirmation experiments.