IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v242y2024ics0951832023006841.html
   My bibliography  Save this article

Dependence assessment in human reliability analysis based on cloud model and best-worst method

Author

Listed:
  • Ji, Changcheng
  • Gao, Fei
  • Liu, Wenjiang

Abstract

Dependence assessment, which is to assess the dependence level of human errors, is an essential part of human reliability analysis, which could be affected by the complexity and uncertainty of the real world. In this paper, a novel dependence assessment method based on cloud model and best-worst method (BWM) is proposed. Firstly, the influential factors used to measure the dependence level are identified. Then, the social network trust graph of different experts is constructed, and the weights of different experts are determined. Next, the cloud model is adopted to represent the linguistic judgments of experts, where the linguistic judgments are transferred into cloud models, and the assessments of different experts are combined. Finally, based on the dependence level of each factor, the final dependence assessment result is obtained. Two numerical examples are presented to show that the proposed method can effectively provide reliable assessment results under uncertainty. In conclusion, the proposed method provides a novel and effective way for dependence assessment in human reliability analysis.

Suggested Citation

  • Ji, Changcheng & Gao, Fei & Liu, Wenjiang, 2024. "Dependence assessment in human reliability analysis based on cloud model and best-worst method," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:reensy:v:242:y:2024:i:c:s0951832023006841
    DOI: 10.1016/j.ress.2023.109770
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023006841
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109770?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bing Wu & Xinping Yan & Yang Wang & C. Guedes Soares, 2017. "An Evidential Reasoning‐Based CREAM to Human Reliability Analysis in Maritime Accident Process," Risk Analysis, John Wiley & Sons, vol. 37(10), pages 1936-1957, October.
    2. Liu, Hu-Chen & Wang, Jing-Hui & Zhang, Ling & Zhang, Qi-Zhen, 2022. "New success likelihood index model for large group human reliability analysis considering noncooperative behaviors and social network," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Liao, Huafei & Groth, Katrina & Stevens-Adams, Susan, 2015. "Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 159-169.
    4. Catelani, Marcantonio & Ciani, Lorenzo & Guidi, Giulia & Patrizi, Gabriele, 2021. "An enhanced SHERPA (E-SHERPA) method for human reliability analysis in railway engineering," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Abreu, Danilo T.M.P. & Maturana, Marcos C. & Droguett, Enrique Lopez & Martins, Marcelo R., 2022. "Human reliability analysis of conventional maritime pilotage operations supported by a prospective model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    6. Peng Liu & Zhizhong Li, 2014. "Human Error Data Collection and Comparison with Predictions by SPAR‐H," Risk Analysis, John Wiley & Sons, vol. 34(9), pages 1706-1719, September.
    7. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zhang, Li & Liu, Xueyang & Ding, Qianqiao & Qin, Zhuomin & ÄŒepin, Marko, 2021. "Analysis of dependencies among performance shaping factors in human reliability analysis based on a system dynamics approach," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan, 2022. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    9. Xiaoyan Su & Sankaran Mahadevan & Peida Xu & Yong Deng, 2015. "Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1296-1316, July.
    10. Luca Podofillini & Vinh Dang & Enrico Zio & Piero Baraldi & Massimo Librizzi, 2010. "Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic," Risk Analysis, John Wiley & Sons, vol. 30(8), pages 1277-1297, August.
    11. Wang, Lijing & Wang, Yanlong & Chen, Yingchun & Pan, Xing & Zhang, Wenjin, 2020. "Performance shaping factors dependence assessment through moderating and mediating effect analysis," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    12. Liu, Hu-Chen & Li, Zhaojun & Zhang, Jian-Qing & You, Xiao-Yue, 2018. "A large group decision making approach for dependence assessment in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 135-144.
    13. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    14. Groth, Katrina M. & Mosleh, Ali, 2012. "A data-informed PIF hierarchy for model-based Human Reliability Analysis," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 154-174.
    15. Baraldi, Piero & Podofillini, Luca & Mkrtchyan, Lusine & Zio, Enrico & Dang, Vinh N., 2015. "Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 176-193.
    16. Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
    17. Ham, Dong-Han & Park, Jinkyun, 2020. "Use of a big data analysis technique for extracting HRA data from event investigation reports based on the Safety-II concept," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    18. Paglioni, Vincent P. & Groth, Katrina M., 2022. "Dependency definitions for quantitative human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(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. Rui Ding & Zehua Liu, 2024. "An IT2FS-ANP- and IT2FS-CM-Based Approach for Conducting Safety Risk Assessments of Nuclear Power Plant Building Projects," Mathematics, MDPI, vol. 12(7), pages 1-20, March.

    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. Wang, Lijing & Wang, Yanlong & Chen, Yingchun & Pan, Xing & Zhang, Wenjin, 2020. "Performance shaping factors dependence assessment through moderating and mediating effect analysis," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    2. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zio, Enrico & Yuan, Chengwei & Wang, Taorui & Jiang, Jianjun, 2022. "A Bayesian belief network framework for nuclear power plant human reliability analysis accounting for dependencies among performance shaping factors," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Patriarca, Riccardo & Ramos, Marilia & Paltrinieri, Nicola & Massaiu, Salvatore & Costantino, Francesco & Di Gravio, Giulio & Boring, Ronald Laurids, 2020. "Human reliability analysis: Exploring the intellectual structure of a research field," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Groth, Katrina M. & Smith, Reuel & Moradi, Ramin, 2019. "A hybrid algorithm for developing third generation HRA methods using simulator data, causal models, and cognitive science," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Paglioni, Vincent P. & Groth, Katrina M., 2022. "Dependency definitions for quantitative human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    7. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    8. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    9. Abrishami, Shokoufeh & Khakzad, Nima & Hosseini, Seyed Mahmoud, 2020. "A data-based comparison of BN-HRA models in assessing human error probability: An offshore evacuation case study," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    10. Park, Jinkyun, 2024. "A framework to determine the holistic multiplier of performance shaping factors in human reliability analysis – An explanatory study," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    11. Zhou, Jian-Lan & Yu, Ze-Tai & Xiao, Ren-Bin, 2022. "A large-scale group Success Likelihood Index Method to estimate human error probabilities in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    12. Kim, Yochan & Kim, Jaewhan & Park, Jinkyun, 2023. "A data-informed dependency assessment of human reliability," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    13. Liu, Peng & Qiu, Yongping & Hu, Juntao & Tong, Jiejuan & Zhao, Jun & Li, Zhizhong, 2020. "Expert judgments for performance shaping Factors’ multiplier design in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    14. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2016. "Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 93-112.
    15. Ekanem, Nsimah & Mosleh, Ali & Shen, Song-Hua & Ramos, Marilia, 2024. "Phoenix–A model-based human reliability analysis methodology: Data sources and quantitative analysis procedure," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    16. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    17. Qiao, Yidan & Zhang, Xian & Wang, Hanyu & Chen, Dengkai, 2024. "Dynamic assessment method for human factor risk of manned deep submergence operation system based on SPAR-H and SD," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    18. Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).
    19. Zhao, Yunfei & Smidts, Carol, 2021. "CMS-BN: A cognitive modeling and simulation environment for human performance assessment, part 1 — methodology," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    20. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(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:eee:reensy:v:242:y:2024:i:c:s0951832023006841. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.