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Investigating the effect of the uncertainty in the parameters on time-varying chatter stability is critical to refrain from the time-varying regenerative chatter in turning. In this study, the influence of tool wear on the cutting force coefficient (CFC) in turning processing is taken into consideration, and CFC variation during cutting time is described by the Gamma process. The model of the time-varying chatter stability in turning is established based on the motional and mechanical properties of the cutting process in turning. Time-varying reliability (TVR) is estimated based on the uncertain and time-varying characteristics of the turning process parameters. The method of moment-independent time-varying global sensitivity analysis (TV-GSA) based on the cumulative failure probability (CFP) is proposed to measure the effect of parameters on the CFP of the chatter stability in turning. Furthermore, for reducing the computational cost of moment-independent TV-GSA based on CFP, the active learning Kriging model is established to replace the nonlinear and implicit limit state function of the chatter stability in turning. The dynamic model of the turning chatter is validated by an illustrative example. And the results of the proposed method are compared with the results of the Monte Carlo simulation to verify the effectiveness of the proposed method.
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