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A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants

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  • Monferini, A.
  • Konstandinidou, M.
  • Nivolianitou, Z.
  • Weber, S.
  • Kontogiannis, T.
  • Kafka, P.
  • Kay, A.M.
  • Leva, M.C.
  • Demichela, M.

Abstract

This paper presents a compound methodology devised to relate Human and Organizational Factors (HOFs) to operators’ response time in critical operations within hazardous industrial plants. The methodology has been based on a sensitivity analysis of the nine “families†of the Common Performance Conditions (CPCs), as defined in the CREAM technique, in order to verify and rank their influence on the operators’ response time. To prove the methodology, a series of pilot experiments have been designed and performed so that human response is evaluated in a Virtual Environment (VE) reproducing the control room and a specific plant section. This environment enables the analyst controlling the simulation to perform the sensitivity analysis acting through a supervisory station and manipulating the control functions in order to vary each CPC rate around its nominal value. Experiments were run with the variation of one CPC at a time aiming at the detection and containment operation of a gas leakage in a pressure-reduction NG terminal. The whole case study has been run within the framework of the VIRTHUALIS EU project.

Suggested Citation

  • Monferini, A. & Konstandinidou, M. & Nivolianitou, Z. & Weber, S. & Kontogiannis, T. & Kafka, P. & Kay, A.M. & Leva, M.C. & Demichela, M., 2013. "A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 280-289.
    • Handle: RePEc:eee:reensy:v:119:y:2013:i:c:p:280-289
    DOI: 10.1016/j.ress.2013.04.012
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    References listed on IDEAS

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    Cited by:

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    3. He, Ye & Kuai, Nian-Sheng & Deng, Li-Min & He, Xiong-Yuan, 2021. "A method for assessing Human Error Probability through physiological and psychological factors tests based on CREAM and its applications," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
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    5. 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.
    6. Musharraf, Mashrura & Bradbury-Squires, David & Khan, Faisal & Veitch, Brian & MacKinnon, Scott & Imtiaz, Syed, 2014. "A virtual experimental technique for data collection for a Bayesian network approach to human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 1-8.
    7. Naderpour, Mohsen & Lu, Jie & Zhang, Guangquan, 2016. "A safety-critical decision support system evaluation using situation awareness and workload measures," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 147-159.
    8. Musharraf, Mashrura & Smith, Jennifer & Khan, Faisal & Veitch, Brian & MacKinnon, Scott, 2016. "Assessing offshore emergency evacuation behavior in a virtual environment using a Bayesian Network approach," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 28-37.

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