Reliability analyses of k-out-of-n: F capability-balanced systems in a multi-source shock environment

• Published in: Reliability engineering & system safety Vol. 227; p. 108733
• Main Authors: Wang, Xiaoyue, Ning, Ru, Zhao, Xian, Zhou, Jian
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2022
• Subjects: k-out-of-n: F capability-balanced system; Multi-source shock environment; Phase-type distribution; Reliability analysis; Two-stage finite Markov chain imbedding approach; Reliability analysis; k-out-of-n: F capability-balanced system; Phase-type distribution; Two-stage finite Markov chain imbedding approach; Multi-source shock environment
• ISSN: 0951-8320
• DOI: 10.1016/j.ress.2022.108733

•A k-out-of-n: F capability-balanced system subject to multi-source shocks is built.•Concept of system capability balance is proposed based on real engineering cases.•The multi-source shock environment is first considered for balanced systems.•A two-stage FMCIA and PH distributions are combined to evaluate system reliability. Research on balanced systems has sparked intense attentions due to their widespread engineering applications. Previous studies all considered that balanced systems operate in a single-source shock environment and the existing concepts of system balance are limited. Nevertheless, some balanced systems operate in more complex shock environment with multiple sources and new system balance requirements can be explored based on real engineering cases. To make up research gaps, this paper proposes a k-out-of-n: F capability-balanced system working in a multi-source shock environment, where the shock impacts from various sources can differ significantly. The components have multiple states owing to shocks and an operating capability is taken for each component state. The concept of system capability balance is defined based on the largest capability difference between components and a random probability of system to keep capability-balanced within a certain range is considered. System failure can be caused by dissatisfying the capability-balanced conditions and reaching the critical number of failed components. A two-stage finite Markov chain imbedding approach and PH distribution are combined to evaluate the probabilistic quantities of the system. Finally, illustrative examples are provided to validate the proposed model and future studies are discussed.