IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v144y2015icp159-169.html
   My bibliography  Save this article

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Author

Listed:
  • Liao, Huafei
  • Groth, Katrina
  • Stevens-Adams, Susan

Abstract

This article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. These challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:144:y:2015:i:c:p:159-169
    DOI: 10.1016/j.ress.2015.07.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015002239
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.07.018?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. Podofillini, L. & Dang, V.N., 2013. "A Bayesian approach to treat expert-elicited probabilities in human reliability analysis model construction," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 52-64.
    2. Preischl, Wolfgang & Hellmich, Mario, 2013. "Human error probabilities from operational experience of German nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 150-159.
    3. James Chang, Y. & Bley, Dennis & Criscione, Lawrence & Kirwan, Barry & Mosleh, Ali & Madary, Todd & Nowell, Rodney & Richards, Robert & Roth, Emilie M. & Sieben, Scott & Zoulis, Antonios, 2014. "The SACADA database for human reliability and human performance," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 117-133.
    4. Groth, Katrina M. & Smith, Curtis L. & Swiler, Laura P., 2014. "A Bayesian method for using simulator data to enhance human error probabilities assigned by existing HRA methods," Reliability Engineering and System Safety, Elsevier, vol. 128(C), pages 32-40.
    5. Park, Jinkyun & Jung, Wondea, 2007. "OPERA—a human performance database under simulated emergencies of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 92(4), pages 503-519.
    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. 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.
    2. Park, Jooyoung & Boring, Ronald L. & Ulrich, Thomas A. & Lew, Roger & Lee, Sungheon & Park, Bumjun & Kim, Jonghyun, 2022. "A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Liao, Huafei & Forester, John & Dang, Vinh N. & Bye, Andreas & Chang, Yung Hsien J. & Lois, Erasmia, 2019. "Assessment of HRA method predictions against operating crew performance: Part III: Conclusions and achievements," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. 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).
    5. 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).

    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. Kim, Yochan & Park, Jinkyun & Jung, Wondea & Jang, Inseok & Hyun Seong, Poong, 2015. "A statistical approach to estimating effects of performance shaping factors on human error probabilities of soft controls," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 378-387.
    2. 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).
    3. Morais, Caroline & Estrada-Lugo, Hector Diego & Tolo, Silvia & Jacques, Tiago & Moura, Raphael & Beer, Michael & Patelli, Edoardo, 2022. "Robust data-driven human reliability analysis using credal networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    4. Jung, Wondea & Park, Jinkyun & Kim, Yochan & Choi, Sun Yeong & Kim, Seunghwan, 2020. "HuREX – A framework of HRA data collection from simulators in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    5. 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).
    6. Preischl, Wolfgang & Hellmich, Mario, 2016. "Human error probabilities from operational experience of German nuclear power plants, Part II," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 44-56.
    7. 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).
    8. Greco, Salvatore F. & Podofillini, Luca & Dang, Vinh N., 2021. "A Bayesian model to treat within-category and crew-to-crew variability in simulator data for Human Reliability Analysis," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    9. Shirley, Rachel Benish & Smidts, Carol & Zhao, Yunfei, 2020. "Development of a quantitative Bayesian network mapping objective factors to subjective performance shaping factor evaluations: An example using student operators in a digital nuclear power plant simul," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    10. Park, Jooyoung & Boring, Ronald L. & Ulrich, Thomas A. & Lew, Roger & Lee, Sungheon & Park, Bumjun & Kim, Jonghyun, 2022. "A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    11. Podofillini, Luca & Reer, Bernhard & Dang, Vinh N., 2023. "A traceable process to develop Bayesian networks from scarce data and expert judgment: A human reliability analysis application," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    12. Kim, Yochan & Park, Jinkyun, 2019. "Incorporating prior knowledge with simulation data to estimate PSF multipliers using Bayesian logistic regression," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 210-217.
    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. Kim, Yochan & Park, Jinkyun & Jung, Wondea & Choi, Sun Yeong & Kim, Seunghwan, 2018. "Estimating the quantitative relation between PSFs and HEPs from full-scope simulator data," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 12-22.
    15. Zwirglmaier, Kilian & Straub, Daniel & Groth, Katrina M., 2017. "Capturing cognitive causal paths in human reliability analysis with Bayesian network models," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 117-129.
    16. 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).
    17. Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A quantitative measure of fitness for duty and work processes for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 595-601.
    18. 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).
    19. Paglioni, Vincent P. & Groth, Katrina M., 2022. "Dependency definitions for quantitative human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    20. Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A classification scheme of erroneous behaviors for human error probability estimations based on simulator data," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 1-13.

    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:144:y:2015:i:c:p:159-169. 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.