Prediction of tool chatter and metal removal rate in turning operation on lathe using a new merged technique

Abstract

Tool chatter is an unstable phenomenon resulting in inaccurate machining and detritions of cutting tool. In this study, a combination of statistical approach and signal pre-processing technique has been adopted to explore the mechanism of tool chatter in turning operation. The effects of cutting parameters: depth of cut (d), feed (f) and spindle speed (N) on chatter have been investigated based on response surface model (RSM). Experimentally acquired raw chatter signals are pre-processed using wavelet transforms in order to remove the ambient noise contents. Further, to examine the influence of aforesaid cutting parameters on chatter severity, a new parameter, called chatter index (CI), has been evaluated. Furthermore, RSM has been adopted to develop quadratic and cubic mathematical models of CI and metal removal rate. Moreover, analysis of variance has been performed to check the statistical significance and combined effect of control parameters on machined output. More experiments have been conducted to validate the developed model. correlation between the predicted and experimental results validates the developed technique of ascertaining the tool chatter severity and metal removal rate.