Abstract: Reliability, maintainability and availability are three important attributes to describe the quality of a large-scale device. A certain large-scale device is in the prototype testing phase and clearly exhibits reliability growth. However, the high environmental stress and operation cost result in the difficulties to collect field data. Moreover, the downtime constraint should be considered when the availability analysis is carried out. Therefore, it is very difficult to carry out device reliability, maintainability and availability assessments. In this paper, the empirical analysis is first carried out based on the field failure and maintenance data, then the device reliability improvement trend is determined with a piecewise linear model. For the small sample question of the field failure and maintenance data, the Bayesian method is introduced, and the field reliability and maintainability parameters are calculated by the soft WinBUGS. Then the most appropriate description of the system availability—mission availability with closed expression form is presented. In order to illustrate the effectiveness of the method, the field data from June 4, 2007 to May 17, 2010 has been couected. Through the case study, two reliability change-points are determined and thus the device reliability and maintainability are analyzed with Bayesian method. As a result, the average relative error of Bayesian and maximum likelihood methods are 0.42% and 8.78% respectively. Then it can be concluded that using the Bayesian method to carry out field reliability analysis is more effective compared to the maximum likelihood method.

Key words: field reliability, maintainability, mission availability, bayesian