Reduction of Tool Wear in EDM Process Using Statistical Analysis and Simulated Annealing Algorithm

in this study the effect of input EDM process parameters on AISI2312, hot worked steel, widely used in mold manufacturing, is modeled and optimized. The proposed approach is based on statistical analysis on the experimental data. The input parameters are peak current, pulse on time and pulse off time, duty factor and voltage. Tool wear rate is one of the most important performance characteristic of the EDM process. Taguchi robust design technique was applied to obtain the signal to noise ratio for the quality characteristics being investigated. In order to establish the relations between the input and the output parameters, various regression functions have been fitted on the evaluated data, based on output characteristic. The significance of the process parameters on the quality characteristic of the EDM process was also evaluated quantitatively using the analysis of variance method. Then, statistical analyses and validation experiments have been carried out to select the best and most fitted model. In the last section of this research, simulated annealing algorithm has been employed for optimizations of process parameters. The results indicate that the proposed modeling technique and simulated annealing algorithm are quite efficient in modeling and optimization of EDM process parameters.