Human error probability evaluation based on reference task using intuitionistic fuzzy theory
•A reference task based human error model is proposed.•Extending the application of IFS in HRA, the TIFN-HRA method was proposed.•Two solutions based on TIFN-HRA are developed to assess HEP.•Both solutions give the same results, with solution I being simpler and easier to use. Human Reliability Anal...
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Veröffentlicht in: | Computers & industrial engineering 2024-05, Vol.191, p.110105, Article 110105 |
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Sprache: | eng |
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Zusammenfassung: | •A reference task based human error model is proposed.•Extending the application of IFS in HRA, the TIFN-HRA method was proposed.•Two solutions based on TIFN-HRA are developed to assess HEP.•Both solutions give the same results, with solution I being simpler and easier to use.
Human Reliability Analysis (HRA) is a critical issue for addressing human error in system reliability. There are numerous tasks for which human factors-related data are not available, rendering expert knowledge the only basis for assessing such tasks. However, the knowledge obtained from experts is subject to ambiguity and vagueness, which affects the usability of the assessment results. To overcome this challenge, in this paper a reference task based HRA method is proposed and the intuitionistic fuzzy set (IFS) is adopted because of its advantage of being able to handle ambiguous information. Firstly, to analyze the human error probability (HEP) of the target task, a reference task-based human error analysis model is introduced. Two solutions are provided: calculating the performance shaping factors (PSFs) distance between the reference task and the target task and establishing a quantitative relationship between PSFs and HEP. Secondly, the PSFs evaluation and inference methods based on triangular intuitionistic fuzzy numbers (TIFNs) are developed. Finally, the effectiveness and consistency of the two solutions of TIFN-HRA are demonstrated through a spaceflight refueling mission analysis. The distances between the results of the two solutions and the expert linguistic are compared and both results have the shortest distance to “Low”. However, solution I is simpler and the result is clearer. |
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ISSN: | 0360-8352 1879-0550 |
DOI: | 10.1016/j.cie.2024.110105 |