Abstract
Hardware systems are present in many fields of human activity. Markov models are sometimes used in hardware reliability, availability, and maintainability (RAM) modeling. They are especially useful in situations in which the system we want to analyze may be modeled with several states through which the system evolves, some of them corresponding to ON states, the rest to OFF states. We provide here RAM analyses of such systems within a Bayesian framework, addressing both short-term and long-term performance.