IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v93y2008i4p567-577.html
   My bibliography  Save this article

An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network

Author

Listed:
  • Lee, Seung Jun
  • Kim, Man Cheol
  • Seong, Poong Hyun

Abstract

The design of instrumentation and control (I&C) systems for nuclear power plants (NPPs) is rapidly moving towards fully digital I&C systems and is trending towards the introduction of modern computer techniques into the design of advanced main control rooms (MCRs) of NPPs. In the design of advanced MCRs, human–machine interfaces have improved and various types of decision support systems have been developed. It is important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate decision support systems in order to validate their efficiency is as important as to design highly reliable decision support systems. In this paper, an operation advisory system based on the human cognitive process is evaluated in order to estimate its effect. The Bayesian belief network model is used in the evaluation of the target system, and a model is constructed based on human reliability analysis event trees. In the evaluation results, a target system based on the operator's cognitive process showed better performance compared to independent decision support systems.

Suggested Citation

  • Lee, Seung Jun & Kim, Man Cheol & Seong, Poong Hyun, 2008. "An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 567-577.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:4:p:567-577
    DOI: 10.1016/j.ress.2007.02.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832007000555
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2007.02.004?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. Kim, Man Cheol & Seong, Poong Hyun, 2006. "A computational method for probabilistic safety assessment of I&C systems and human operators in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 580-593.
    2. Kim, Man Cheol & Seong, Poong Hyun, 2006. "An analytic model for situation assessment of nuclear power plant operators based on Bayesian inference," Reliability Engineering and System Safety, Elsevier, vol. 91(3), pages 270-282.
    3. Kim, Jong Hyun & Seong, Poong Hyun, 2007. "The effect of information types on diagnostic strategies in the information aid," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 171-186.
    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. Jo, Wooseok & Lee, Seung Jun, 2024. "Human reliability evaluation method covering operator action timing for dynamic probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    3. Wang, Wei & Di Maio, Francesco & Zio, Enrico, 2020. "Considering the human operator cognitive process for the interpretation of diagnostic outcomes related to component failures and cyber security attacks," Reliability Engineering and System Safety, Elsevier, vol. 202(C).

    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. 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.
    2. Naderpour, Mohsen & Lu, Jie & Zhang, Guangquan, 2015. "An abnormal situation modeling method to assist operators in safety-critical systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 33-47.
    3. Simeu-Abazi, Zineb & Lefebvre, Arnaud & Derain, Jean-Pierre, 2011. "A methodology of alarm filtering using dynamic fault tree," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 257-266.
    4. Ha, Jun Su & Seong, Poong Hyun, 2009. "A human–machine interface evaluation method: A difficulty evaluation method in information searching (DEMIS)," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1557-1567.
    5. Lee, Hyun-Chul & Seong, Poong-Hyun, 2009. "A computational model for evaluating the effects of attention, memory, and mental models on situation assessment of nuclear power plant operators," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1796-1805.
    6. Kim, Man Cheol & Seong, Poong Hyun, 2008. "A method for identifying instrument faults in nuclear power plants possibly leading to wrong situation assessment," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 316-324.
    7. Park, Jinkyun & Jung, Wondea & Yang, Joon-Eon, 2012. "Investigating the effect of communication characteristics on crew performance under the simulated emergency condition of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 1-13.
    8. Sýkora, Miroslav & Marková, Jana & Diamantidis, Dimitris, 2018. "Bayesian network application for the risk assessment of existing energy production units," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 312-320.

    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:93:y:2008:i:4:p:567-577. 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.