Using Markov regenerative process assesses reliability and steady-state probabilities in repairable systems, highlighting maintenance impacts.
Abstract This paper analyzes a (A +W + C): repairable system with multiple standby components using Markov Regenerative Stochastic Petri Nets (MRSPNs). The system includes corrective and preventive maintenance with a single repairer prone to breakdowns. Failed components are repaired immediately when the repairer is available, otherwise they join a First-Come, First-Served orbit queue. The MRSPN framework models the system behavior, the associated Markov regenerative process is used to compute steady-state probabilities for availability analysis. Reliability function and time-to-first-failure estimation are performed using Markov renewal equation combined with Laplace transforms. Numerical examples demonstrate how system parameters affect performance and reliability metrics. Mathematics Subject Classification: 60K15 , 90B25, 60K20
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BOUDEHANE et al. (2025) studied this question.
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