Stability analysis of cnc lathe for higher material removal rate

Abstract

Self-excited vibration (regenerative chatter) in machining processes has been investigated by several researchers and still many aspects within this domain are yet to be explored. It is a major hurdle in attaining higher metal removal rate with good surface quality in most of the machining processes including turning, milling and drilling. Regenerative chatter is harmful to all the machining processes as it creates excessive vibration between the tool and work piece, thereby resulting in poor surface finish, high-pitch noise and accelerated tool wear which in turn reduces machine tool life, reliability, and safety of the machining operation. In this thesis, both theoretical and experimental works have been carried out to predict, detect and investigate tool chatter. In the theoretical analysis; mathematical modeling, simulation, stability lobe diagram has been drawn and discussed. In the experimental analysis; experiments have been performed on CNC lathe at different combinations of cutting parameters and the chatter signals have been recorded using a microphone. These recorded signals have been processed using signal processing techniques viz. wavelet transform, empirical mode decomposition (EMD), and ensemble empirical mode decomposition (EEMD). These processed signals have been further used to calculate the output parameters (chatter severity). Moreover, the metal removal rate has also been evaluated at the corresponding range of cutting parameters. These output parameters (chatter severity and metal removal rate) have been explored by developing prediction models in order to establish the relation between the input and output parameters using response surface methodology (RSM) and artificial neural network (ANN).