Optimal switching and condition-based maintenance of cold standby systems subject to competitive failure and imperfect switchover

Abstract

Cold standby redundant structures can improve system reliability and availability but are subjected to internal degradation and external shocks during operation. Thus, the switching process in a standby system is prone to failures. This study investigates the optimal switching and condition-based maintenance (CBM) decision of a two-unit cold standby system subject to mutually dependent competitive failure processes with an imperfect switchover. First, periodic switching and offline CBM policies under imperfect switchover are proposed; second, the reliability models of competitive failure—between soft failure caused by system degradation subject to nonfatal shock and hard failure caused by fatal shock—are established. An iterative model of the system state probability distribution is subsequently derived by analysing the characteristics of state transitions in alternate use and maintenance of the active and standby units. An analytical decision model is also established to minimise the average cost rate in a finite horizon to obtain the optimal switching period and maintenance threshold. Finally, a case study of a coal mine main ventilator system validates the proposed model.

Keywords:

• Cold standby system
• competing failure process
• imperfect switchover
• condition-based maintenance
• optimal decision

Acknowledgements

The authors also gratefully acknowledge the helpful comments and suggestions from the anonymous reviewers, which significantly helped to improve this paper.

Disclosure statement

The authors have no competing interests to declare that are relevant to the content of this article. We do not analyse or generate any datasets, because our work proceeds within a theoretical and mathematical approach.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

The authors would like to thank the National Natural Science Foundation of China (72071183; 71701140); Basic Research Program Project in Shanxi Province (202203021211194; 20210302124680; 202103021223291) Research Project Supported by Shanxi Scholarship Council of China (2022-161;2021-135) Key Research Bases Project for Humanities and Social Sciences of Higher Education Institutions in Shanxi (20220123; 20210102) Taiyuan University of Science and Technology Graduate Joint Training Demonstration Base Project (JD2022008; JD2022010) Taiyuan University of Science and Technology Scientific Research Initial Funding (20202027; 20202028).