Reliability modeling and analysis of cycloid gear grinding machines based on the bootstrap-bayes method

Abstract

To increase the reliability of cycloidal wheel grinding machines, reduce the failure rate of machine tools, and shorten maintenance times, a reliability modeling method for small-sample fault data is proposed based on the Bootstrap-Bayes method. The mean time between failures (MTBF) of a machine tool generally conforms to a Weibull distribution. Based on the historical fault information and similar fault information, the distribution function for the mean time between failures of a machine tool is determined. The fault information is expanded by the self-help method, and the two-parameter distribution interval of the distribution function is calculated by the Bayesian formula. An example reliability calculation for a cycloid gear grinding machine is given, including the failure analysis and maintenance methods of the gear grinding machine. This approach can also be used to simulate and analyze the reliability of other computer numerical control (CNC) machine tools.