An Empirical Study on Modeling and Optimization of EDM Process Parameters for Inconel 718 Super Alloy Using D-optimal approach and Genetic Algorithm

Abstract

In this study the effect of input parameters of electrical discharge machining (EDM) process on Inconel 718 super alloy, widely used in aircraft and spacecraft industries, nuclear power systems and steam generators, etc., are been studied. The proposed approach is based on statistical analysis on the experimental data gathered using D-optimal design. Material removal rate (MRR) and surface roughness (SR) are the most important performance characteristics of the EDM process have been studied. In order to establish the relations between the input and the output parameters, various regression functions have been fitted on the data based on output characteristics. The significance of the process parameters on the quality characteristics of the EDM process was also evaluated quantitatively using the analysis of variance (ANOVA) method. Then, statistical analyses and validation experiments have been carried out to compare and select the best and the most fitted models. In the last section of this research, genetic algorithm (GA) has been employed for optimization of the process characteristics. Using the proposed optimization procedure, proper levels of input parameters for any desirable group of process outputs can be identified. A set of verification tests is also performed to verify the accuracy of optimization procedure in determining the optimal levels of machining parameters. The results indicate that the proposed modeling technique and genetic algorithm are quite efficient in modeling and optimization of EDM process parameters.