Prediction of machining performances in powder mixed electro-discharge machining to process skd61 steel by response surface methodology

Abstract

In electro-discharge machining (EDM) with mixing powder, it is called powder mixed electro-discharge machining (PMEDM), then machining performances- i.e. material removal rate(MRR) and tool wear rate (TWR) has great significance in evaluating the effectiveness and machining accuracy of the machining method. Therefore, in this study, response surface methodology (RSM) was utilized for estimating functions of process variables {comprising peak current (Ip), pulse on time (Ton), and powder concentration (Cp)} for the machining performances for processing SKD61 steel during EDM process with tungsten compound powder. Box-Behnken matrix was utilized for designing and conducting a series of empirical trials. Analysis of variance (ANOVA) was applied to evaluate the adequate of predictive models. The outcomes reveal that the predicted models of MRR and TWR have a high precision with R2 values of MRR and TWR being 99.2% and 99.11%, respectively. The error comparison of the predictive and empirical values for the confirmed experiments is less than 5%, this once again consolidates that the developed models' accuracy. These development models can efficiently prognosticate the desired machining performances of the PMEDM method for processing SKD61 steel