Mathematical Modeling and Optimization of Material Removal Rate in EDM Process Using Design of Experiments and Genetic Algorithm

electrical discharge machining (EDM) is themost widely and successfully applied for the machining ofconductive parts. In this process, the tool has no mechanicalcontact with the specimen and the hardness of work piece hasno effect on the machining pace. Hence, this technique couldbe employed to machine hard materials such as super alloys.Inconel 718 super alloy is a nickel based alloy that is mostlyused in oil and gas, power stations and aerospace industries.In this study the effect of input EDM process parameters onInconel 718 super alloy, is modeled and optimized. Theprocess input parameters considered here include voltage(V), peak current (I), pulse on time (Ton) and duty factor (η).The process quality measure is material removal rate (MRR).The objective is to determine a combination of processparameters to maximize MRR. The experimental data aregathered based on D-optimal design of experiments (DOE).Then, statistical analyses and validation experiments havebeen carried out to select the best and most fitted regressionmodels. In the last section of this research, genetic algorithm(GA) has been employed for optimization of the performancecharacteristics. Using the proposed optimization procedure,proper levels of input parameters for any desirable group ofprocess outputs can be identified. A set of verification tests isalso performed to verify the accuracy of optimizationprocedure in determining the optimal levels of machiningparameters. The results indicate that the proposed modelingtechnique and genetic algorithm are quite efficient inmodeling and optimization of EDM process parameters.

کلیدواژه ها:

Electrical Discharge Machining (EDM) ، Inconel 718 super alloy ، Optimization ، Genetic Algorithm (GA) ، Analysis of Variance (ANOVA)