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Fuzzy inference system based prediction of electrical discharge machining quality
Quality and productivity are two most important performances of electrical discharge machining (EDM). This paper presents the application of a fuzzy inference system (FIS) for prediction of machining quality in the EDM process. Specifically, the FIS conducted modeling of geometrical accuracy and surface finish of EDM machined parts. With the fuzzy inference system model, the input variables are discharge current and pulse duration, while the output parameters are gap distance between the electrodes and surface roughness of the workpiece. The performance of the proposed FIS provides a more effective selection of the EDM input values, which leads to better machining conditions and quality of the final product. The fuzzy inference system based modeling of the EDM process showed a very good agreement compared to the experimental data.
Fuzzy inference system based prediction of electrical discharge machining quality
Quality and productivity are two most important performances of electrical discharge machining (EDM). This paper presents the application of a fuzzy inference system (FIS) for prediction of machining quality in the EDM process. Specifically, the FIS conducted modeling of geometrical accuracy and surface finish of EDM machined parts. With the fuzzy inference system model, the input variables are discharge current and pulse duration, while the output parameters are gap distance between the electrodes and surface roughness of the workpiece. The performance of the proposed FIS provides a more effective selection of the EDM input values, which leads to better machining conditions and quality of the final product. The fuzzy inference system based modeling of the EDM process showed a very good agreement compared to the experimental data.
Fuzzy inference system based prediction of electrical discharge machining quality
Gostimirović Marin P. (author) / Rodić Dragan Đ. (author) / Sekulić Milenko L.J. (author)
2021
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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