Optimization of EDM Process Parameters Using Statistical Analysis and SimulatedAnnealing Algorithm

Nowadays, electrical discharge machining (EDM) has become one of the most extensively used nontraditionalmaterial removal processes. Its unique feature of using thermal energy to machine hard-tomachineelectrically conductive materials is its distinctive advantage in the manufacturing of moulds,dies and aerospace components. However, EDM is a costly process and hence proper selection of itsprocess parameters is essential to reduce production cost and improve product quality. In this study theeffect of input EDM process parameters on AISI2312 hot worked steel, widely used in moldmanufacturing, is modeled and optimized. The proposed approach is based on statistical analysis onthe experimental data. The input parameters are peak current (I), pulse on time (Ton), pulse off time(Toff), duty factor (?) and voltage (V). Material removal rate (MRR), tool wear rate (TWR), andsurface roughness (SR) are the most important performance characteristics of the EDM process. Theexperimental data are gathered using Taguchi L36 design matrix. Taguchi robust design technique wasapplied to obtain the signal to noise ratio (S/N ratio) for the quality characteristics being investigated.In order to establish the relations between the input and the output parameters, various regressionfunctions have been fitted on the evaluated S/Ns data based on output characteristics. The significanceof the process parameters on the quality characteristics of the EDM process was also evaluatedquantitatively using the analysis of variance (ANOVA) method. Then, statistical analyses andvalidation experiments have been carried out to select the best and most fitted models. In the lastsection of this research, simulated annealing (SA) algorithm has been employed for optimization of theperformance characteristics. Using the proposed optimization procedure, proper levels of inputparameters for any desirable group of process outputs can be identified. A set of verification tests isalso performed to verify the accuracy of optimization procedure in determining the optimal levels ofmachining parameters. The results indicate that the proposed modeling technique and simulatedannealing algorithm are quite efficient in modeling and optimization of EDM process parameters.