Bayesian Accelerated Reliability Growth of Complex Systems

Today's competitive global business environment and continually increasing product complexity have created a need to shorten product development time while guaranteeing high reliability for customers. In this context, reliability growth programs and accelerated life testing (ALT) have become the tools of choice to help companies achieve their product reliability goals as fast as possible. One of the most popular statistical models for analyzing reliability growth data is the Crow-AMSAA model, which struggles to incorporate ALT data when the product has multiple failure modes. Moreover, key system components may be developed independently and without incorporating the testing results in the product reliability estimation. Thus, companies may be performing unnecessary testing at the system level.