Space Product Reliability Evaluation in Two-Stage Development Based on Scaling Factor

Space products have high reliability and will experience multi-stage development with respective tests after each stage. Due to the limit of budget and time-to-market, the tests usually have small sample sizes and short durations. A few or no failures are more likely to appear in such tests for high-reliability products. In practical engineering, reliability assessment will not be satisfactory if only depending on data from the current test. And this problem will be improved if multi-stage data is included. In this paper, a scaling factor method is adopted to deal with the conversion problem of the data in the previous stage. Then the Bayesian posteriori estimations of the reliability parameters are obtained by the Markov Chain Monte Carlo (MCMC) sampling method. After two-dimensional integral is calculated, the confidence lower limit of reliability can be given accurately. A case study is carried out to illustrate the effectiveness of the proposed method.