2.5 Markov Process
As discussed in Section 2.3, the state space‐based methods belong to the analytical methods for system reliability analysis. Among the state space‐based methods, Markov models particularly, continuous‐time Markov chains (CTMCs) have commonly been applied to analyze reliability of systems with dynamic behavior and exponential component ttf distributions [7, 15 ].
Constructing a Markov model involves identifying system states and possible transitions among these states. In the Markov‐based system reliability analysis, each state typically denotes a distinct combination of failed and functioning components. A state transition governs the change of the system from one state to another state due to events such as failure of a component or repair of a component. Each state transition is characterized by certain parameter(s), such as a component's failure rate or repair rate [56]. The state transition diagram starts with an initial state ...