Prediction of Performance Measures in Wire Electrical Discharge Machining of Aluminum–Fly Ash Composites Using Regression Analysis

Abstract

Wire electrical discharge machining (WEDM) is one among the contemporary method of material removal process which is established from the perception of spark erosion machining. Non-traditional method of material removal processes has been evolved to overcome some difficulties in making of intricate shapes in any electrically conductive work material. Decision making is increasing fractious in the manufacturing domain because of its need for manufacturing the quality components with high precision and rapid changes in design. This present exploration deals with the evolvement of multiple regression equations for predicting the desired performance measures in wire EDM process. The experimental trials are devised with the help of Taguchi’s experimental design approach, and the empirical equations are established using multiple regression models. Analysis of variance (ANOVA) is adopted for determining the importance of process variables which affects the desired performance measures. The evolved method for prediction of desired performance measures is flexible, competent, and accurate than existing models, and it scopes a better monitoring system. Finally, the evolved models are validated. The predicted results based on the developed models are in better covenant with the experimental outcomes.