Generalized mixed shock model for multi-component systems in the shock environment with a change point

Xiaoyue Wang, Ru Ning, Xian Zhao*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    Abstract

    The reliability of various systems under shock models has been explored extensively in the literature, where the constant mechanism of shock impact has always been studied. Nevertheless, engineering systems operate in a more complicated shock environment due to developments, and it is worth studying the reliability of such multi-component systems in a variable shock environment. Driven by the research gaps and practical situations, this paper constructs a reliability model of multi-component systems under a generalized mixed shock model with a change point. The multi-state components operate in the shock environment I initially and it may continue to run in the shock environment II after the random change point of the environment. Two novel shock impact mechanisms of the variable environment are put forward, where a series of failure criteria based on shocks are included. Four different structures of multi-component systems are considered in this paper. It can be proved that the proposed mixed shock model is a generalization of some transformed models. A multi-stage finite Markov chain imbedding approach is established to derive the probabilistic indices of the components and entire systems. Based on the engineering applications, illustrative examples are provided to verify the effectiveness of the proposed model.

    Original languageEnglish
    Pages (from-to)619-635
    Number of pages17
    JournalProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    Volume237
    Issue number4
    DOIs
    Publication statusPublished - Aug 2023

    Keywords

    • Generalized mixed shock model
    • multi-component system
    • multi-stage finite Markov chain imbedding approach
    • random change point
    • reliability analysis

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