Fuzzy approach to select machining parameters in electrical discharge machining (EDM) and ultrasonic-assisted EDM processes

Abstract Condition monitoring of the machining process is very important in today's precision manufacturing, especially in the electrical discharge machining (EDM). This paper introduces a fuzzy-based algorithm for prediction of material removal rate (MRR), tool wear ratio (TWR), and surface roughness ( R z , R k ) in the EDM and ultrasonic-assisted EDM (US/EDM) processes. In this system, discharge current, pulse duration, and ultrasonic vibration of tool are the input variables and outputs are MRR, TWR, R z , and R k . The proposed fuzzy model in this study provides a more precise and easy selection of EDM and US/EDM input parameters, respectively for the required MRR, TWR, R z , and R k , which leads to better machining conditions and decreases the machining costs. The fuzzy modeling of EDM and US/EDM were able to predict the experimental results with accuracies more than 90%.

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