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Analysis of Team Situation Awareness Errors in Digital Nuclear Power Plants

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 778)

Abstract

In the digital main control rooms (MCRs) of nuclear power plants (NPPs), the role and responsibility of operators as well as their communication ways are changed by the digitization of the human-machine interface, which leads to some new team situation awareness (TSA) errors and different error distribution. In order to identify the interaction mechanism among a team during collecting information and consistently understanding the system/component status, an team interaction model is established by field observation, video analysis, operator interview and event report analysis. Furthermore, the model-based TSA error classification is developed and the influencing factors of TSA error are identified. On this basis, a number of human factor event reports are analyzed and combining with statistical analysis to identify the main TSA errors and influencing factors in digital NPPs. It provides theoretical support for the prevention and control of TSA errors.

Keywords

Team situation awareness Performance Influencing Factors Human factor event report Digital nuclear power plants 

Notes

Acknowledgments

The financial support by the National Natural Science Foundation of China (No. 51674145, 71771084), Postdoctoral Science Foundation of China (No. 2016M600633), Natural Science Foundation of Hunan Province (No. 2017JJ2222), Humanities and Social Science Projects of Ministry of Education (No. 11YJC630207) and Social Science Projects of Hunan Province (No. 16YBA314) are gratefully acknowledged. We would like to express gratitude to the staff in a Chinese nuclear power plant (LingAo-II) for the interviews and investigations, which facilitate the research included in this paper.

References

  1. 1.
    Lelardeux, C.P., Panzoli, D., Lubrano, V., et al.: Communication system and team situation awareness in a multiplayer real-time learning environment: application to a virtual operating room. Vis. Comput. 33, 489–515 (2017)Google Scholar
  2. 2.
    Werner, W.F., Hirano, M., Kondo, S., et al.: Results and insights from level-a probabilistic safety assessments for nuclear power plants in France, Germany, Japan, Sweden, Switzerland, and the United States. Reliab. Eng. Syst. Saf. 48, 165–179 (1995)CrossRefGoogle Scholar
  3. 3.
    Reason, J.: A Life in Error. Ashgate Publishing Ltd., Farnham (2013)Google Scholar
  4. 4.
    Reason, J.: Human error: models and management. Br. Med. J. 320(7237), 768–770 (2000)CrossRefGoogle Scholar
  5. 5.
    Kim, S.K., Park, J.Y., Byun, S.N.: Crew resource management training for improving team performance of operators in Korean advanced nuclear power plant. In: IEEE International Conference on Industrial Engineering and Engineering Management, pp. 2055–2059. IEEE Press, Hong Kong (2009)Google Scholar
  6. 6.
    Lin, C.J., Yenn, T.C., Yang, C.W.: Evaluation of operators’ performance for automation design in the fully digital control room of nuclear power plants. Hum. Factors Ergon. Manuf. Serv. Ind. 20, 10–23 (2010)CrossRefGoogle Scholar
  7. 7.
    Lin, C.J., Hsieh, T.L., Yang, C.W., Huang, R.J.: The impact of computer-based procedures on team performance, communication, and situation awareness. Int. J. Ind. Ergon. 51, 21–29 (2016)CrossRefGoogle Scholar
  8. 8.
    Sasou, K., Reason, J.: Team errors: definition and taxonomy. Reliab. Eng. Syst. Saf. 65, 1–9 (1999)CrossRefGoogle Scholar
  9. 9.
    Chung, Y.H., Yoon, W.C., Min, D.: A model-based framework for the analysis of team communication in nuclear power plants. Reliab. Eng. Syst. Saf. 94, 1030–1040 (2009)CrossRefGoogle Scholar
  10. 10.
    Li, P.C., Dai, L.C., Zhang, L., et al.: Cognitive processes and PEMs of TSA in digitized MCRs of NPPs. In: AHFE2017. Springer, Los Angeles (2017)Google Scholar
  11. 11.
    O’Connor, P., O’Dea, A., Flin, R., Belton, S.: Identifying the team skills required by nuclear power plant operations personnel. Int. J. Ind. Ergon. 38(11), 1028–1037 (2008)CrossRefGoogle Scholar
  12. 12.
    Whaley, A.M., Xing, J., Boring, R.L.: Cognitive Basis for Human Reliability Analysis. Technical report, NUREG-2114, United States Nuclear Regulatory Commission, Washington, DC (2016)Google Scholar
  13. 13.
    Hollnagel, E.: Human Reliability Analysis: Context and Control. Academic Press, London (1993)Google Scholar
  14. 14.
    Groth, K.M.: A Data-Informed Model of Performance Shaping Factors for Use in Human Reliability Analysis. University of Maryland, College Park (2009)Google Scholar
  15. 15.
    Kaber, D.B., Endsley, M.R.: Team situation awareness for process control safety and performance. Process Saf. Prog. 17(1), 43–48 (1998)CrossRefGoogle Scholar
  16. 16.
    Salmon, P.M., Stanton, N.A., Walker, G.H., et al.: What really is going on? Review of situation awareness model for individuals and teams. Theor. Issues Ergon. Sci. 9(4), 297–323 (2008)CrossRefGoogle Scholar
  17. 17.
    Stanton, N.A., Salmon, P.M., Walker, G.H., et al.: Genotype and phenotype schemata as models of situation awareness in dynamic command and control teams. Int. J. Ind. Ergon. 39, 480–489 (2009)CrossRefGoogle Scholar
  18. 18.
    Kim, S.C., Lee, D.H., Lee, J.I.: Empirical investigation of team performance evaluation on crew composition and procedure type. In: ANS Probabilistic Safety Assessment Top Meeting, Park City Utah (1996)Google Scholar
  19. 19.
    Li, P.C., Chen, G.H., Dai, L.C., Zhang, L.: A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks. Saf. Sci. 50(7), 1569–1583 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Human Factor InstituteUniversity of South ChinaHengyangPeople’s Republic of China
  2. 2.School of Nuclear Science and TechnologyUniversity of South ChinaHengyangPeople’s Republic of China

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