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Competing risks-based resilience approach for multi-state systems under multiple shocks

Dui, Hongyan, Lu, Yaohui, Wu, Shaomin (2024) Competing risks-based resilience approach for multi-state systems under multiple shocks. Reliability Engineering and System Safety, 242 . Article Number 109773. ISSN 0951-8320. (doi:10.1016/j.ress.2023.109773) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:103664)

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Effective measurement of system resilience provides a comprehensive understanding of the system’s characteristics. However, little research has been devoted to the resilience of a technical system that is affected by both the degradation process of the system and the external shocks. In addition, existing studies have mainly evaluated the resilience of systems without considering competing risks, and rarely investigated the transient resilience evaluation subjected to the interaction of shocks and maintenance. In this paper, a new resilience model is proposed for the systems under competing risks. The paper first introduces a competing risk model to depict the failure modes of the single-component system, and then uses semi-Markov processes to describe the state transition process when the system suffers the attacks of multiple shocks. Then, according to the multi-state division of the system, a resistibility index, an absorbability index and a recoverability index are proposed and the overall resilience is then introduced. Considering that the system needs to meet the reliability requirement, constrained by limit budget for maintenance, a reliability and cost-based resilience model is proposed. Finally, the case of a radar system subjected to shocks of one type and multiple types of shocks is given to illustrate the concept developed in this paper.

Item Type: Article
DOI/Identification number: 10.1016/j.ress.2023.109773
Uncontrolled keywords: Competing risks; Resilience; System reliability; Condition-based maintenance; Semi-Markov process
Subjects: H Social Sciences > HA Statistics
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: University of Kent (
Depositing User: Shaomin Wu
Date Deposited: 03 Nov 2023 15:35 UTC
Last Modified: 09 Jan 2024 08:20 UTC
Resource URI: (The current URI for this page, for reference purposes)

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