Fuzzy approach to select machining parameters in electrical discharge machining (EDM) and ultrasonic-assisted EDM processes |
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| Authors: | MR Shabgard MA Badamchizadeh G Ranjbary K Amini |
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| Affiliation: | 1. Department of Manufacturing Engineering, University of Tabriz, Tabriz, Iran;2. Department of Electrical & Computer Engineering, University of Tabriz, Tabriz, Iran;3. Department of Mechanical, Automotive and Materials Engineering, University of Windsor, Windsor, Ontario, Canada |
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| 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 (Rz, Rk) 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, Rz, and Rk. 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, Rz, and Rk, 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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| Keywords: | ANFIS adaptive neuro-fuzzy inference system DOE design of experiments EDM electrical discharge machining L large M medium ML medium large MRR material removal rate RBFN radial basis function networks S small TANMLP hyperbolic tangent sigmoid multi-layered perceptron TWR tool wear ratio US/EDM ultra-assisted electrical discharge machining VL very large VS very small |
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