Vishal Parashar

Optimization of Machining Parameters in Electro Discharge Machining of Al6061-Cu-SiC-Graphite Metal Matrix Composite

The newly fabricated hybrid metal matrix composite of Al 6061 reinforced with wt. % of Cu/Sic/Graphite is prepared by a stir casting route. Electrical discharge machining (EDM) is employed to machine this MMC with copper electrode. The purpose of this study is to investigate the second order mathematical model in terms of machining constraints were developed for Material removal rate prediction. The adequacy of the model on MRR has been established with a statistical analysis of variance (ANOVA) to investigate the influence of process parameters and their interactions. Further this model is processed with help of Genetic Algorithm (GA) to find out the optimum machining parameters. The best result for maximum MRR using GA are carried out to show a good agreement with the predicted results.

Performance Measurement and Data Analysis of Material Removal Rate for Wire Cut Electro Discharge Machining Process

In this paper, statistical and regression analysis of material removal rate using design of experiments is proposed for WEDM operations. Experimentation was planned as per Taguchi’s mixed orthogonal array. Each experiment has been performed under different cutting conditions of gap voltage, pulse ON time, pulse OFF time, wire feed and dielectric flushing pressure. Stainless Steel grade 304L was selected as a work material to conduct the experiments. From experimental results, the material removal rate was determined for each machining performance criteria. Analysis of variance (ANOVA) technique was used to find out the variables affecting the material removal rate. Assumptions of ANOVA were discussed and carefully examined using analysis of residuals. Variation of the material removal rate with machining parameters was mathematically modeled by using the regression analysis method. The developed model was validated with a set of experimental data and appeared to be satisfactory. Signal to noise ratio was applied to measure the performance characteristics deviating from the actual value. Finally, experimental confirmation was carried out to identify the effectiveness of this proposed method.