Bayesian Methods for Estimating the Reliability of Complex Systems Using Heterogeneous Multilevel Information
We propose a Bayesian approach for assessing the reliability of multicomponent systems. Our models allow us to evaluate system, subsystem, and component reliability using the available multilevel information. Data are collected over time, and include pass/fail, lifetime, censored, and degradation data. We illustrate the methodology through an example and discuss how to extend the approach to more complex systems.
This preprint was published as Jiqiang Guo & Alyson G. Wilson, "Bayesian Methods for Estimating System Reliability Using Heterogeneous Multilevel Information", Technometrics (2013): 461-472, doi: 10.1080/00401706.2013.804441.