Abstract
In this paper, experimental investigation and estimation of surface roughness using optimization techniques -Artificial Neural Network (ANN), Group method data handling (GMDH) and multiple regression analysis (MRA) inhigh speed micro end milling of titanium alloy (grade-5)were presented. A comparative study was made to know the influence of spindle speed, feed and depth of cut on surface roughness of Ti-6Al-4V-titanium alloy. From the observations, it is clearly seen that prediction accuracy of neural network is higher than other techniques that is in good agreement with experimental values.
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