Optimizing the maximum filling level of perfect storage in system with imperfect production unit

Gregory Levitin, Liudong Xing and Yuanshun Dai

Reliability Engineering and System Safety, 2022, vol. 225, issue C

Abstract: 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 Cmax on the mission success probability (MSP). This paper contributes by modeling two-sided effects of Cmax 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 Cmax 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 Cmax 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 Cmax.

Keywords: Storage filling; Random repair time; Mission success (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:225:y:2022:i:c:s095183202200268x

DOI: 10.1016/j.ress.2022.108629

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