Abstract
ABSTRACT Tool chatter is an ineluctable phenomenon encountered frequently in turning process. In the present work, statistical approach along with signal pre-processing has been adopted to explore the mechanism of tool chatter in turning operation. Experiments have been performed to acquire raw chatter signals. Wavelet transforms have been used for pre-processing these signals in order to remove the ambient noise contents. Further, response surface methodology (RSM) has been adopted to develop quadratic and cubic mathematical models of tool chatter considering three cutting parameters: depth of cut (d), feed (f) and spindle speed (N). In order to examine the influence of aforesaid cutting parameters on chatter severity, a new parameter called chatter index has been evaluated. Moreover, analysis of variance has been performed to check the statistical significance and combined effect of control parameters on machined output. The results have been analysed using regression plots and 3D surface graphs. More experiments have been conducted to validate the developed model. Well correlation between the predicted and experimental results validates the developed technique of ascertaining the tool chatter severity.
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