Dynamic stability simulation of micro-milling under the condition of multi-parameter uncertainty

Abstract

A stable processing state is the continuous pursuit of manufacturing process engineering. The premise of predicting the cutting stability boundary lies in understanding the dynamic mechanism of the machining process. In addition, parameter uncertainty and measurement errors may lead to inconsistency between the simulated and the test value. In this paper, a novel dynamic micro-milling system framework is developed, which takes into account multiple parameter uncertainties, including the tool runout, the coupling effect, the size effect, the process damping, and the distribution of the cutting coefficients and model parameters. The dynamic mechanical models of the shearing and ploughing dominant regions are established, and the state transition matrix is constructed using a discrete method. The prior probability information of relevant machining parameters is obtained based on the reception coupling theory, error convergence method, and experimental data. The accuracy of the posterior parameters under reliability updates is verified by combining the experimental results, the Adaptive Bayesian Updating based on the Structural reliability analysis method, and the presented mechanical model. The proposed dynamic framework can be applied universally for the steady-state analysis of the practical machining process.