Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where the electrically conductive powder is mixed into the dielectric fluid to enhance the machining efficiency. In this investigation, PMEDM is performed for the machining of AISI 304 stainless steel when silicon carbide powder is mixed into the kerosene dielectric. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) are considered as response. A face centered central composite design (FCCCD) based response surface methodology (RSM) is applied to design the experiment. A hybrid optimization technique like desirability coupled with fuzzy-logic method is performed to get the optimum level of the multiple performance characteristics. Analysis of variance (ANOVA) is performed for the statistical analysis. The result shows that peak current is the most significant parameter for MRR, TWR and Ra. The optimal setting for maximum MRR, minimum TWR and Ra have been obtained by desirability coupled with fuzzy-logic method.
Powder mixed electro discharge machining (PMEDM) is a hybrid machining process where electrically conductive powder is suspended into a dielectric medium, for enhancing the material removal as well as the surface finish. In this investigation, electro discharge machining (EDM) has been performed for the machining of AISI 304 stainless steel by using the tungsten carbide electrode, when silicon carbide (SiC) powder is suspended into kerosene dielectric medium. Peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameter while the surface roughness (Ra) is the only response. The effect of significant process parameters on the response has been studied. A regression analysis has been performed to describe the correlation of data between the machining parameter, and the response. Microstructural analysis has been done for the PMEDMed surface. The result shows that peak current is the most influential parameter for surface roughness. Surface roughness decreases with the increase of powder concentration.