Reliability Growth Model Based on Bayesian Parameter Inference

Reliability growth is to improve the reliability performance of the system by simulating the reliability evolution of the system during the testing process, which relies on the establishment of reliability models. This paper proposes a reliability growth modeling method based on Bayesian parameter inference. As data continues to be acquired, the distribution can be updated to obtain more accurate reliability parameters. Since the parameter distribution of the model will gradually become more complex during the update process, the parameter distribution is simplified to make its prior and posterior distribution have a conjugate relationship, and the feasibility of the method is verified by simulation experiments.