IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v194y2020ics0951832017310402.html
   My bibliography  Save this article

The evaluation of fatigue as a performance shaping factor in the Petro-HRA method

Author

Listed:
  • Rasmussen, Martin
  • Laumann, Karin

Abstract

In the development of the Petro-HRA method [5], a human reliability analysis (HRA) developed for the petroleum industry, a number of factors believed to effect human performance were reviewed and considered for inclusion in the method's performance shaping factor (PSF) taxonomy. The method was created for prospective risk analysis of post-initiator events and it was created as a method that focused on including the most important PSFs, rather than attempting to include all aspects of human performance. This paper assess whether fatigue should be among the PSFs included. This article presents: (1) how fatigue is included in current human reliability methods; (2) fatigue and its underlying aspects; (3) how these aspects affect performance and; (4) the consideration of including fatigue as a PSF in Petro-HRA. Four possible PSFs based on the causes of are suggested: Sleep deprivation, Shift-length, Non-day shift, and Prolonged task performance. However, due to the relative low impacts of the PSFs and the Petro-HRA's focus on only the strongest PSFs, the final method did not include any of the suggested fatigue PSFs.

Suggested Citation

  • Rasmussen, Martin & Laumann, Karin, 2020. "The evaluation of fatigue as a performance shaping factor in the Petro-HRA method," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:reensy:v:194:y:2020:i:c:s0951832017310402
    DOI: 10.1016/j.ress.2018.06.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017310402
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2018.06.015?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. Skogdalen, Jon Espen & Vinnem, Jan Erik, 2011. "Quantitative risk analysis offshore—Human and organizational factors," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 468-479.
    2. Laumann, Karin & Rasmussen, Martin, 2016. "Suggested improvements to the definitions of Standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) performance shaping factors, their levels and multipliers and the nominal tasks," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 287-300.
    3. Griffith, Candice D. & Mahadevan, Sankaran, 2015. "Human reliability under sleep deprivation: Derivation of performance shaping factor multipliers from empirical data," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 23-34.
    4. Griffith, Candice D. & Mahadevan, Sankaran, 2011. "Inclusion of fatigue effects in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1437-1447.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Taylor, Claire & Øie, Sondre & Gould, Kristian, 2020. "Lessons learned from applying a new HRA method for the petroleum industry," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    3. Patriarca, Riccardo & Ramos, Marilia & Paltrinieri, Nicola & Massaiu, Salvatore & Costantino, Francesco & Di Gravio, Giulio & Boring, Ronald Laurids, 2020. "Human reliability analysis: Exploring the intellectual structure of a research field," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. 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.
    5. Liu, Peng & Lyu, Xi & Qiu, Yongping & He, Jiandong & Tong, Jiejuan & Zhao, Jun & Li, Zhizhong, 2017. "Identifying key performance shaping factors in digital main control rooms of nuclear power plants: A risk-based approach," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 264-275.
    6. 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).
    7. Kasai, Naoya & Matsuhashi, Shigemi & Sekine, Kazuyoshi, 2013. "Accident occurrence model for the risk analysis of industrialfacilities," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 71-74.
    8. 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.
    9. Teng, Kuei-Yung & Thekdi, Shital A. & Lambert, James H., 2012. "Identification and evaluation of priorities in the business process of a risk or safety organization," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 74-86.
    10. Burns, Kevin & Bonaceto, Craig, 2020. "An empirically benchmarked human reliability analysis of general aviation," Reliability Engineering and System Safety, Elsevier, vol. 194(C).
    11. Zhang, Yan & Wang, Yu-Hao & Zhao, Xu & Tong, Rui-Peng, 2023. "Dynamic probabilistic risk assessment of emergency response for intelligent coal mining face system, case study: Gas overrun scenario," Resources Policy, Elsevier, vol. 85(PB).
    12. Che, Haiyang & Zeng, Shengkui & Zhao, Yingzhi & Guo, Jianbin, 2024. "Reliability assessment of multi-state weighted k-out-of-n man-machine systems considering dependent machine deterioration and human fatigue," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    13. Gressgård, Leif Jarle & Hansen, Kåre, 2015. "Knowledge exchange and learning from failures in distributed environments: The role of contractor relationship management and work characteristics," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 167-175.
    14. Dina Guglielmi & Alessio Paolucci & Valerio Cozzani & Marco Giovanni Mariani & Luca Pietrantoni & Federico Fraboni, 2022. "Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector," IJERPH, MDPI, vol. 19(5), pages 1-17, February.
    15. Peng Liu & Zhizhong Li, 2014. "Human Error Data Collection and Comparison with Predictions by SPAR‐H," Risk Analysis, John Wiley & Sons, vol. 34(9), pages 1706-1719, September.
    16. Mitra Hannani & Marc Bascompta & Mojtaba Gerami Sabzevar & Hesam Dehghani & Ali Asghar Khajevandi, 2023. "Causal Analysis of Safety Risk Perception of Iranian Coal Mining Workers Using Fuzzy Delphi and DEMATEL," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    17. Di Pasquale, Valentina & Miranda, Salvatore & Iannone, Raffaele & Riemma, Stefano, 2015. "A Simulator for Human Error Probability Analysis (SHERPA)," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 17-32.
    18. Li, Zhengbing & Feng, Huixia & Liang, Yongtu & Xu, Ning & Nie, Siming & Zhang, Haoran, 2019. "A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    19. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zio, Enrico & Yuan, Chengwei & Wang, Taorui & Jiang, Jianjun, 2022. "A Bayesian belief network framework for nuclear power plant human reliability analysis accounting for dependencies among performance shaping factors," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Park, Jinkyun, 2024. "A framework to determine the holistic multiplier of performance shaping factors in human reliability analysis – An explanatory study," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

    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:194:y:2020:i:c:s0951832017310402. 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.