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Human factor risk management in the process industry: A case study

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  • Bevilacqua, Maurizio
  • Ciarapica, Filippo Emanuele

Abstract

In this work, a new procedure called Human Factor Risk Management (HFRM) was developed in order to integrate Human Factor in a Refinery Risk Management System. Taking into consideration historical data regarding Environmental Accidents, Near miss, Injuries and Operating accidents occurred in a refinery over the last years a panel of experts defined the performance shaping factors (PSFs) and risk associated with adverse events. A conceptual model, based on Association Rules (AR), has been proposed for investigating the network of influences among adverse event typology, human error causes, refinery plant area involved in the adverse event, performance shaping factors (PSFs), risk index and corrective actions.

Suggested Citation

  • Bevilacqua, Maurizio & Ciarapica, Filippo Emanuele, 2018. "Human factor risk management in the process industry: A case study," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 149-159.
    • Handle: RePEc:eee:reensy:v:169:y:2018:i:c:p:149-159
    DOI: 10.1016/j.ress.2017.08.013
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Grosse, E. H. & Glock, C. H. & Jaber, M. Y., 2013. "The effect of worker learning and forgetting on storage reassignment decisions in order picking systems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62648, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Martins, Marcelo Ramos & Maturana, Marcos Coelho, 2013. "Application of Bayesian Belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 89-109.
    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. Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
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    Citations

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    Cited by:

    1. 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).
    2. Ewa DUDEK & Karolina KRZYKOWSKA-PIOTROWSKA & Mirosław SIERGIEJCZYK, 2020. "Risk Management In (Air) Transport With Exemplary Risk Analysis Based On The Tolerability Matrix," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 15(2), pages 143-156, June.
    3. Jia, Xiaohui & Zhang, Donghui, 2021. "Prediction of maritime logistics service risks applying soft set based association rule: An early warning model," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    4. Maurizio Bevilacqua & Eleonora Bottani & Filippo Emanuele Ciarapica & Francesco Costantino & Luciano Di Donato & Alessandra Ferraro & Giovanni Mazzuto & Andrea Monteriù & Giorgia Nardini & Marco Orten, 2020. "Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants," Sustainability, MDPI, vol. 12(3), pages 1-17, February.
    5. Antonello, Federico & Baraldi, Piero & Shokry, Ahmed & Zio, Enrico & Gentile, Ugo & Serio, Luigi, 2021. "Association rules extraction for the identification of functional dependencies in complex technical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    6. 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.
    7. Zhou, Jian-Lan & Tu, Ren-Fang & Xiao, Hai, 2022. "Large-scale group decision-making to facilitate inter-rater reliability of human-factors analysis for the railway system," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    8. Huiyue Diao & Majid Ghorbani, 2018. "Production risk caused by human factors: a multiple case study of thermal power plants," Frontiers of Business Research in China, Springer, vol. 12(1), pages 1-27, December.
    9. Wenjun Zhang & Xiangkun Meng & Xue Yang & Hongguang Lyu & Xiang-Yu Zhou & Qingwu Wang, 2022. "A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H," IJERPH, MDPI, vol. 19(16), pages 1-14, August.

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