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- W2187724124 abstract "The present study highlights the application of box-behnken design coupled with fuzzy and regression modeling approach for making expert system in hard milling process to improve the process performance with systematic reduction of production cost. The important input fields of work piece hardness, nose radius, feed per tooth, radial depth of cut and axial depth cut were considered. The cutting forces, work surface temperature and sound pressure level were identified as key index of machining outputs. The results indicate that the fuzzy logic and regression modeling technique can be effectively used for the prediction of desired responses with less average error variation. Predicted results were verified by experiments and shown the good potential characteristics of the developed system for automated machining environment." @default.
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- W2187724124 date "2014-04-25" @default.
- W2187724124 modified "2023-10-14" @default.
- W2187724124 title "Fuzzy and Regression Modelling of Hard Milling Process" @default.
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- W2187724124 doi "https://doi.org/10.19026/rjaset.7.685" @default.
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