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A new method for estimating human error probabilities: AHP–SLIM

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  • Park, Kyung S.
  • Lee, Jae in

Abstract

Accidents in industrial settings are mainly a result of human errors (HEs); relevant fields that consider HEs have recently increased in number. For this reason, numerous methods to quantitatively estimate what is known as the HE probability (HEP) have been developed. However, it is difficult to obtain empirical data, which forces a heavy reliance on the judgment of experts in the field. During the process of judgments by experts, subjectivity plays an important role, causing difficulties in assuring consistency. To overcome this problem and to obtain a more accurate estimation, this study suggests a new and simple method. This method is referred to as AHP–SLIM, a type of HEP estimation using an analytic hierarchy process (AHP), which quantifies the subjective judgment and confirms the consistency of collected data. This new method also uses the process of expert judgment within the success likelihood index method (SLIM).

Suggested Citation

  • Park, Kyung S. & Lee, Jae in, 2008. "A new method for estimating human error probabilities: AHP–SLIM," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 578-587.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:4:p:578-587
    DOI: 10.1016/j.ress.2007.02.003
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    Cited by:

    1. Kyriakidis, Miltos & Majumdar, Arnab & Ochieng, Washington Y., 2018. "The human performance railway operational index—a novel approach to assess human performance for railway operations," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 226-243.
    2. Zhou, Jian-Lan & Lei, Yi, 2020. "A slim integrated with empirical study and network analysis for human error assessment in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    3. Kayisoglu, Gizem & Gunes, Bunyamin & Besikci, Elif Bal, 2022. "SLIM based methodology for human error probability calculation of bunker spills in maritime operations," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    4. Sun, Zhiqiang & Li, Zhengyi & Gong, Erling & Xie, Hongwei, 2012. "Estimating Human Error Probability using a modified CREAM," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 28-32.
    5. Liu, Hu-Chen & Wang, Jing-Hui & Zhang, Ling & Zhang, Qi-Zhen, 2022. "New success likelihood index model for large group human reliability analysis considering noncooperative behaviors and social network," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    6. Zhou, Jian-Lan & Lei, Yi & Chen, Yang, 2019. "A hybrid HEART method to estimate human error probabilities in locomotive driving process," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 80-89.
    7. Elliott, Michael A., 2010. "Selecting numerical scales for pairwise comparisons," Reliability Engineering and System Safety, Elsevier, vol. 95(7), pages 750-763.
    8. Chen, Yuanjiang & Feng, Wei & Jiang, Zhiqiang & Duan, Lingling & Cheng, Shuangyi, 2021. "An accident causation model based on safety information cognition and its application," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    9. Su, Xiaoyan & Mahadevan, Sankaran & Xu, Peida & Deng, Yong, 2014. "Inclusion of task dependence in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 128(C), pages 41-55.
    10. De Ambroggi, Massimiliano & Trucco, Paolo, 2011. "Modelling and assessment of dependent performance shaping factors through Analytic Network Process," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 849-860.
    11. Quigley, John & Hardman, Gavin & Bedford, Tim & Walls, Lesley, 2011. "Merging expert and empirical data for rare event frequency estimation: Pool homogenisation for empirical Bayes models," Reliability Engineering and System Safety, Elsevier, vol. 96(6), pages 687-695.

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