Reliability modeling of machining center spindle based on Boosttrap-Bayes

The reliability model established using traditional statistical method for the spindle in machining center with small sample size may be biased in the real case. Therefore, a modified reliability modeling method for small sample size was proposed using Bootstrap-Bayes approach. First, the reliability function of time between failures using empirical modeling method was established. Then the accurate of the parameters prior distribution of Bayes method was provided. This method improves the precision of prior distribution built by traditional empirical method. In order to calculate the posterior distribution of parameters, Monte Carlo simulation was developed. Finally, a real-world example of the spindle of one kind of machining center was presented using the proposed approach to show its potential application. The results show that the proposed method can provide an accurate reliability model for small sample failure data.