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• W2938206535 endingPage "581" @default.
• W2938206535 startingPage "563" @default.
• W2938206535 abstract "This investigation has designed a tool condition monitoring system (TCM) while milling of Inconel 625 based on sound and vibration signatures. The experiments were carried out based on response surface methodology (RSM) central composite design, design of experiments. The process parameters such as speed, feed, depth of cut and vegetable-based cutting fluids were optimized based on surface roughness, flank wear. It was found that the sound pressure and vibration signatures have the direct relation with flank wear. The statistical features like root mean square, skewness, kurtosis and mean values were extracted from the experimental data. From the designed NN estimator, the cutting tool flank wear was predicted with the mean square error (MSE) of 0.084212." @default.
• W2938206535 created "2019-04-25" @default.
• W2938206535 creator A5037601784 @default.
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• W2938206535 date "2019-11-19" @default.
• W2938206535 modified "2023-09-25" @default.
• W2938206535 title "Tool Condition Monitoring While Using Vegetable Based Cutting Fluids During Milling of Inconel 625" @default.
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• W2938206535 doi "https://doi.org/10.1142/s0219686719500306" @default.
• W2938206535 hasPublicationYear "2019" @default.
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