Abstract
This paper presents a new technique to evaluate the stable cutting zone with enhanced metal removal rate in turning operation. Experiments have been conducted at various levels of cutting parameters: depth of cut, feed rate, and spindle speed. Acquired raw chatter signals have been preprocessed using wavelet transforms in order to remove the ambient noise contents. Response surface methodology has been adopted to develop mathematical models of chatter severity and metal removal rate (MRR). Further, multi-objective genetic algorithm technique has been invoked in order to establish the stable cutting zones with maximized MRR. Good correlation between the predicted and experimental results validates the developed technique of ascertaining tool chatter severity and metal removal rate.
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