Experimental and predictive study by multi-output fuzzy model of electrical discharge machining performances

The nature of electrical discharge machining makes it difficult to predict or even measure machining performance, which is why great attention has been paid to methodologies for measuring these performances. In this work, an experimental approach for measuring machining electrical discharge performance and geometric errors was presented. This can improve the authenticity of the parameters measured. A technique for identifying machining parameters using a multi-output system based on fuzzy logic has been proposed. The objective was to determine the influence of machining parameters on the machining performance and associated geometric errors. It is shown that the fuzzy model is capable of giving results providing a good correlation between the real and predicted values. The average error of the model was approximately 1.51% for material removal rate, 3.386% for tool wear rate, 2.924% for wear rate, 5.285% for surface roughness, 4.004% for radial overcut, 4.381% for circularity, and 2.937% for cylindricity.

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