IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i14p3151-d1196265.html
   My bibliography  Save this article

Redundancy-Based Resilience Optimization of Multi-Component Systems

Author

Listed:
  • Hongyan Dui

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Xinyue Wang

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Haohao Zhou

    (Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China)

Abstract

Systems are damaged due to various disturbances, and the reliability of the systems is reduced. Measures to improve system resilience need to be studied since many systems still need to operate normally after suffering damage. In this paper, the whole process of the disturbance and recovery of the system is considered, and a resilience optimization model of a multi-component system is proposed. Firstly, a system resilience assessment method is proposed based on system reliability, and the system resilience loss is used as the resilience assessment index. Secondly, two component importance indexes, loss importance and recovery importance, are proposed for the system disturbance phase and recovery phase, respectively. The two importance indexes are weighted to obtain the weighted importance so as to measure the change law of system resilience and determine the influence degrees of components on system reliability. Then, under the constraint of maintenance time, an optimization model is established to determine a redundancy strategy to maximize system resilience. Finally, through an example analysis of a wind turbine system with its main components, it is verified that the redundancy strategy proposed with this method can reduce the loss of system resilience and effectively improve system reliability.

Suggested Citation

  • Hongyan Dui & Xinyue Wang & Haohao Zhou, 2023. "Redundancy-Based Resilience Optimization of Multi-Component Systems," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3151-:d:1196265
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/14/3151/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/14/3151/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Wang, Nanxi & Wu, Min & Yuen, Kum Fai, 2023. "Assessment of port resilience using Bayesian network: A study of strategies to enhance readiness and response capacities," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Hongyan Dui & Yulu Zhang & Yun-An Zhang, 2023. "Grouping Maintenance Policy for Improving Reliability of Wind Turbine Systems Considering Variable Cost," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
    4. Dui, Hongyan & Wei, Xuan & Xing, Liudong, 2023. "A new multi-criteria importance measure and its applications to risk reduction and safety enhancement," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    5. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    6. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    7. Hongyan Dui & Huiting Xu & Yun-An Zhang, 2022. "Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
    8. Zhou, Jian & Coit, David W. & Felder, Frank A. & Tsianikas, Stamatis, 2023. "Combined optimization of system reliability improvement and resilience with mixed cascading failures in dependent network systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    10. Hongyan Dui & Yuheng Yang & Yun-an Zhang & Yawen Zhu, 2022. "Recovery Analysis and Maintenance Priority of Metro Networks Based on Importance Measure," Mathematics, MDPI, vol. 10(21), pages 1-20, October.
    11. Liu, Meili & Qi, Xiaogang & Pan, Hao, 2022. "Optimizing communication network geodiversity for disaster resilience through shielding approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianxiong Gao & Yuanyuan Liu & Yiping Yuan & Fei Heng, 2023. "Residual Strength Modeling and Reliability Analysis of Wind Turbine Gear under Different Random Loadings," Mathematics, MDPI, vol. 11(18), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Hongyan Dui & Yulu Zhang & Yun-An Zhang, 2023. "Grouping Maintenance Policy for Improving Reliability of Wind Turbine Systems Considering Variable Cost," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
    3. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Janssens, Jochen & Talarico, Luca & Sörensen, Kenneth, 2016. "A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 221-230.
    5. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    7. Armioun, Majid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Siano, Pierluigi, 2023. "Optimal scheduling of CCHP-based resilient energy distribution system considering active microgrids' multi-carrier energy transactions," Applied Energy, Elsevier, vol. 350(C).
    8. Rocco, Claudio M. & Hernandez-Perdomo, Elvis & Mun, Johnathan, 2021. "Assessing manufacturing flow lines under uncertainties in processing time: An application based on max-plus equations, multicriteria decisions, and global sensitivity analysis," International Journal of Production Economics, Elsevier, vol. 234(C).
    9. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    10. Han, Lin & Zhao, Xudong & Chen, Zhilong & Gong, Huadong & Hou, Benwei, 2021. "Assessing resilience of urban lifeline networks to intentional attacks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    11. Landegren, Finn & Höst, Martin & Möller, Peter, 2018. "Simulation based assessment of resilience of two large-scale socio-technical IT networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 112-125.
    12. Gama Dessavre, Dante & Ramirez-Marquez, Jose E. & Barker, Kash, 2016. "Multidimensional approach to complex system resilience analysis," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 34-43.
    13. Ouyang, Min & Liu, Chuang & Xu, Min, 2019. "Value of resilience-based solutions on critical infrastructure protection: Comparing with robustness-based solutions," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    14. Li, Ruiying & Gao, Ying, 2022. "On the component resilience importance measures for infrastructure systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 36(C).
    15. Xiaohe Zhang & Haixiao Pan, 2023. "Community Resilience in Accessing Essential Service Facilities Considering Equity and Aging Demand: A Case of Shanghai, China," Land, MDPI, vol. 12(12), pages 1-21, December.
    16. Ivo Häring & Mirjam Fehling-Kaschek & Natalie Miller & Katja Faist & Sebastian Ganter & Kushal Srivastava & Aishvarya Kumar Jain & Georg Fischer & Kai Fischer & Jörg Finger & Alexander Stolz & Tobias , 2021. "A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid, gas network, and ultrasound localization system," Environment Systems and Decisions, Springer, vol. 41(2), pages 286-329, June.
    17. Xiang He & Yongbo Yuan, 2019. "A Framework of Identifying Critical Water Distribution Pipelines from Recovery Resilience," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3691-3706, September.
    18. Zhao, S. & Liu, X. & Zhuo, Y., 2017. "Hybrid Hidden Markov Models for resilience metrics in a dynamic infrastructure system," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 84-97.
    19. Claudio M Rocco & Kash Barker & Jose Moronta & Jose E Ramirez-Marquez, 2018. "Community detection and resilience in multi-source, multi-terminal networks," Journal of Risk and Reliability, , vol. 232(6), pages 616-626, December.
    20. HOSSAIN, Niamat Ullah Ibne & Amrani, Safae El & Jaradat, Raed & Marufuzzaman, Mohammad & Buchanan, Randy & Rinaudo, Christina & Hamilton, Michael, 2020. "Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3151-:d:1196265. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.