Continuous-Time Markov Processes for Reliability Analysis: A Comprehensive Study

Abstract

As industrial computer systems become increasingly vital in various industries, ensuring their reliability and security is paramount. This paper presents an innovative technique for evaluating the reliability of such systems using Markov chain models. These models capture the dynamic interactions between different system components, enabling the generation of a state transition diagram. By deriving steady-state differential equations from this diagram, the method can determine steady-state probabilities, revealing the system's availability and performance indicators. This approach contrasts with static methods like fault tree analyses and reliability block diagrams, which focus solely on structural properties and cannot often account for dynamic system behavior. The technique has been successfully applied to diverse industrial systems, aiding in preventing reliability issues and enhancing user and environmental safety.