System reliability assessment as components undergo accelerated testing

Accelerated testing (AT) is widely used to demonstrate and assess product reliability and is especially useful for products with long life and high reliability requirements. Currently, research is primarily focused on test planning, acceleration model and parameter estimation for AT of specific products, such as electronic and mechanical components, etc. In our application, for several components of the system undergoing AT we desire to obtain the system reliability at the lower limit confidence, which is a considerable issue. However little research on this issue is presently available. This paper proposes a feasible method, which converts component data from AT to equivalent binomial component data and then estimates the approximate lower limit confidence (ALLC) of system reliability using a Bayesian method. A numerical example is illustrated to verify that the proposed method is better than the alternative methods by Monte Carlo (MC) simulation. Eventually, the method is applied to the assessment of storage reliability for a safety valve.