IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i12p2707-d1171510.html
   My bibliography  Save this article

Negentropy as a Measure to Evaluate the Resilience in Industrial Plants

Author

Listed:
  • Orlando Durán

    (Escuela de Ingeniería Mecánica, Pontificia Universidad Católica de Valparaíso, Valparaíso 2430120, Chile)

  • Gustavo Sáez

    (Escuela de Ingeniería Mecánica, Pontificia Universidad Católica de Valparaíso, Valparaíso 2430120, Chile)

  • Paulo Durán

    (Universidad Católica Silva Henríquez, Santiago 8330225, Chile)

Abstract

Resilience is an essential quality of systems. This characteristic is based on the ability of a system to cope with disruptive events. To prevent decreases in system functionality and performance and to respond promptly to unexpected situations or shocks, systems must possess this capacity. One challenge lies in identifying and measuring resilience. Recently, various metrics have been proposed in the literature to represent the resilience of systems. Despite this, there is still no global resilience measure that can be used in any type of industrial system. This work investigated a series of moment statistics and explored the field of entropy in the search for a general resilience indicator. A set of 27 hypothetical cases were proposed to calculate the indices under evaluation. Then, a series of comparisons were made between these indices and two resilience indicators found in the literature. The main results of this work lead to the overall conclusion that it is possible to use some of these indicators as potential resilience indicators for engineering systems and production lines. Specifically, negentropy appears to be a good option for this purpose.

Suggested Citation

  • Orlando Durán & Gustavo Sáez & Paulo Durán, 2023. "Negentropy as a Measure to Evaluate the Resilience in Industrial Plants," Mathematics, MDPI, vol. 11(12), pages 1-15, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:12:p:2707-:d:1171510
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/12/2707/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/12/2707/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feng, Qiang & Zhao, Xiujie & Fan, Dongming & Cai, Baoping & Liu, Yiqi & Ren, Yi, 2019. "Resilience design method based on meta-structure: A case study of offshore wind farm," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 232-244.
    2. Cai, Baoping & Xie, Min & Liu, Yonghong & Liu, Yiliu & Feng, Qiang, 2018. "Availability-based engineering resilience metric and its corresponding evaluation methodology," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 216-224.
    Full references (including those not matched with items on IDEAS)

    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. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    2. Cai, Baoping & Zhang, Yanping & Wang, Haifeng & Liu, Yonghong & Ji, Renjie & Gao, Chuntan & Kong, Xiangdi & Liu, Jing, 2021. "Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    3. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    4. Eldosouky, AbdelRahman & Saad, Walid & Mandayam, Narayan, 2021. "Resilient critical infrastructure: Bayesian network analysis and contract-Based optimization," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    5. Dui, Hongyan & Liu, Meng & Song, Jiaying & Wu, Shaomin, 2023. "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Caputo, A.C. & Donati, L. & Salini, P., 2023. "Estimating resilience of manufacturing plants to physical disruptions: Model and application," International Journal of Production Economics, Elsevier, vol. 266(C).
    7. Niamat Ullah Ibne Hossain & Farjana Nur & Raed Jaradat & Seyedmohsen Hosseini & Mohammad Marufuzzaman & Stephen M. Puryear & Randy K. Buchanan, 2019. "Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    8. Ren, Yi & Fan, Dongming & Feng, Qiang & Wang, Zili & Sun, Bo & Yang, Dezhen, 2019. "Agent-based restoration approach for reliability with load balancing on smart grids," Applied Energy, Elsevier, vol. 249(C), pages 46-57.
    9. Fangyu Liu & Hongyan Dui & Ziyue Li, 2022. "Reliability analysis for electrical power systems based on importance measures," Journal of Risk and Reliability, , vol. 236(2), pages 317-328, April.
    10. Fan, Dongming & Sun, Bo & Dui, Hongyan & Zhong, Jilong & Wang, Ziyao & Ren, Yi & Wang, Zili, 2022. "A modified connectivity link addition strategy to improve the resilience of multiplex networks against attacks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    11. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    12. Eichhorn Colombo, Konrad W., 2023. "Financial resilience analysis of floating production, storage and offloading plant operated in Norwegian Arctic region: Case study using inter-/transdisciplinary system dynamics modeling and simulatio," Energy, Elsevier, vol. 268(C).
    13. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    14. Adumene, Sidum & Khan, Faisal & Adedigba, Sunday & Zendehboudi, Sohrab & Shiri, Hodjat, 2021. "Dynamic risk analysis of marine and offshore systems suffering microbial induced stochastic degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    15. Yeh, Wei-Chang & Chu, Ta-Chung, 2018. "A novel multi-distribution multi-state flow network and its reliability optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 209-217.
    16. Watson, Bryan C & Morris, Zack B & Weissburg, Marc & Bras, Bert, 2023. "System of system design-for-resilience heuristics derived from forestry case study variants," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    17. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    18. Xiahou, Tangfan & Zheng, Yi-Xuan & Liu, Yu & Chen, Hong, 2023. "Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    19. Meng, Huixing & Kloul, Leïla & Rauzy, Antoine, 2018. "Modeling patterns for reliability assessment of safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 111-123.
    20. Zhang, Chao & Xu, Xin & Dui, Hongyan, 2020. "Resilience Measure of Network Systems by Node and Edge Indicators," Reliability Engineering and System Safety, Elsevier, vol. 202(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:12:p:2707-:d:1171510. 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.