Reliability of production systems with storage has recently attracted lots of research attentions. While the existing works have assumed certain maximum capacity of the storage, no models are available to examine the effects of the storage's maximum filling level C-max on the mission success probability (MSP). This paper contributes by modeling two-sided effects of C-max on the MSP of an imperfect production system subject to repairs and preventive maintenance (PM) during the specified mission time. In particular, a larger value of C-max enables the storage to supply the system demand during a longer time when the production system is under repair or PM (enhancing the MSP); on the other hand, it leads to longer operation periods and consequently more frequent failures of the production system (reducing the MSP). To balance these conflicting effects, we formulate and solve the optimal storage filling problem, which determines the optimal value of C-max to maximize the MSP. The optimization solution encompasses a new probabilistic model-based numerical algorithm proposed for the MSP evaluation. A case study of a water pump system is performed to demonstrate the influences of several system parameters and their interactions on the MSP and optimized C-max.
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