IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v248y2024ics0951832024002266.html
   My bibliography  Save this article

A method for safety analysis of human-machine systems based on dynamic Bayesian simulation

Author

Listed:
  • Pan, Xing
  • Du, Hengte
  • Yu, Haofan

Abstract

Accidents in human-machine systems often lead to serious consequences, so safety analysis is very important for such systems. However, the existing approach to safety analysis of human-machine systems lacks clear delineation of the coupling relationships between human and machine, or provide quantitative analysis. To address these issues, this paper proposes a method for safety analysis of human-machine systems, utilizing dynamic Bayesian network (DBN) and dynamic fault tree (DFT). The core of this method is the identification of human-machine coupling relationships, proposing 10 types of logical relationships and presenting corresponding DFT logic. Then, a conversion method from DFT to DBN is designed to avoid combinatorial explosion in complex FTA calculations. Based on the DBN model, simulation is conducted using Gibbs sampling, which offers higher computational efficiency. Additionally, a method for importance analysis is devised to identify critical nodes that impact the system risk. At last, a case study of refueling mission at space launch site is given to illustrate how to apply the method. Through simulation analysis, the safety risks during the refueling mission are quantitatively assessed, while critical nodes are identified. The results indicate that the dynamic Bayesian simulation method is good in information utilization, dynamic representation, and time performance.

Suggested Citation

  • Pan, Xing & Du, Hengte & Yu, Haofan, 2024. "A method for safety analysis of human-machine systems based on dynamic Bayesian simulation," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:reensy:v:248:y:2024:i:c:s0951832024002266
    DOI: 10.1016/j.ress.2024.110152
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832024002266
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2024.110152?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. Haiyue Yu & Xiaoyue Wu, 2021. "A method for transformation from dynamic fault tree to binary decision diagram," Journal of Risk and Reliability, , vol. 235(3), pages 416-430, June.
    2. Hu, Yunwei & Parhizkar, Tarannom & Mosleh, Ali, 2022. "Guided simulation for dynamic probabilistic risk assessment of complex systems: Concept, method, and application," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    3. Che, Haiyang & Zeng, Shengkui & Guo, Jianbin, 2019. "Reliability assessment of man-machine systems subject to mutually dependent machine degradation and human errors," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    4. Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Che, Haiyang, 2021. "A Bayesian network for reliability assessment of man-machine phased-mission system considering the phase dependencies of human cognitive error," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    5. Li, Chenzhao & Mahadevan, Sankaran, 2018. "Efficient approximate inference in Bayesian networks with continuous variables," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 269-280.
    6. Pan, Xing & Zuo, Dujun & Zhang, Wenjin & Hu, Lunhu & Wang, Huixiong & Jiang, Jing, 2021. "Research on Human Error Risk Evaluation Using Extended Bayesian Networks with Hybrid Data," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    7. Zeng, Zhiguo & Barros, Anne & Coit, David, 2023. "Dependent failure behavior modeling for risk and reliability: A systematic and critical literature review," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    8. Lu, Qin & Zhang, Wei, 2022. "Integrating dynamic Bayesian network and physics-based modeling for risk analysis of a time-dependent power distribution system during hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    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. Che, Haiyang & Zeng, Shengkui & Zhao, Yingzhi & Guo, Jianbin, 2024. "Reliability assessment of multi-state weighted k-out-of-n man-machine systems considering dependent machine deterioration and human fatigue," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    2. 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).
    3. Che, Haiyang & Zeng, Shengkui & Li, Kehui & Guo, Jianbin, 2022. "Reliability analysis of load-sharing man-machine systems subject to machine degradation, human errors, and random shocks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Hughes, William & Zhang, Wei & Cerrai, Diego & Bagtzoglou, Amvrossios & Wanik, David & Anagnostou, Emmanouil, 2022. "A Hybrid Physics-Based and Data-Driven Model for Power Distribution System Infrastructure Hardening and Outage Simulation," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. He, Rui & Zhu, Jingyu & Chen, Guoming & Tian, Zhigang, 2022. "A real-time probabilistic risk assessment method for the petrochemical industry based on data monitoring," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Xiao, Yong & Wei, Shanbi & Chai, Yi & Pan, Tianle & Hou, Yang, 2023. "Reliability optimization of flexible test system based on pyro-mechanical device products production driven," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    8. You, Qidong & Guo, Jianbin & Zeng, Shengkui & Che, Haiyang, 2024. "A dynamic Bayesian network based reliability assessment method for short-term multi-round situation awareness considering round dependencies," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    9. Nazarizadeh, Farzaneh & Alemtabriz, Akbar & Zandieh, Mostafa & Raad, Abbas, 2022. "An analytical model for reliability assessment of the rail system considering dependent failures (case study of Iranian railway)," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    10. Garg, Vipul & Vinod, Gopika & Kant, Vivek, 2023. "Auto-CREAM: Software application for evaluation of HEP with basic and extended CREAM for PSA studies," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    11. Davies, Katherine & Dembińska, Anna, 2024. "On the residual lifetimes of dependent components upon system failure," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    12. Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    13. Feng, Jian Rui & Zhao, Meng-ke & Lu, Shou-xiang, 2024. "Accident spread and risk propagation mechanism in complex industrial system network," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    14. Å arÅ«nienÄ—, Inga & MartiÅ¡auskas, Linas & KrikÅ¡tolaitis, RiÄ ardas & Augutis, Juozas & Setola, Roberto, 2024. "Risk assessment of critical infrastructures: A methodology based on criticality of infrastructure elements," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    15. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system considering common cause failure: Based on a beta-factor and continuous-time bayesian network model," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    16. Atul Patil & Chaitanya Pathak & Bejoy Alduse, 2023. "Review of Natural Hazard Risks for Wind Farms," Energies, MDPI, vol. 16(3), pages 1-29, January.
    17. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    18. Adedipe, Tosin & Shafiee, Mahmood & Zio, Enrico, 2020. "Bayesian Network Modelling for the Wind Energy Industry: An Overview," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    19. Feng, Jian Rui & Yu, Guanghui & Zhao, Mengke & Zhang, Jiaqing & Lu, Shouxiang, 2022. "Dynamic risk assessment framework for industrial systems based on accidents chain theory: The case study of fire and explosion risk of UHV converter transformer," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2022. "Optimal loading of repairable system with perfect product storage," Reliability Engineering and System Safety, Elsevier, vol. 220(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:248:y:2024:i:c:s0951832024002266. 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.