Digesting human-related incidents in nuclear power plant commissioning – Part I: An integrated methodology

Zijian Yin, Boyang Gong, Zhaopeng Liu, Dongfang Yang, Shanguang Chen and Zhizhong Li

Reliability Engineering and System Safety, 2025, vol. 262, issue C

Abstract: This study aims to take advantage of incident data to enhance human reliability analysis (HRA) and safety management, with the research presented in two parts. Part I of this article reports the methodology for incident coding and analysis. Generally, human-related incident analysis aims to answer WHAT can go wrong (the failed task), HOW it can go wrong (the human error mode), and WHY it went wrong (the contextual factors). To address these questions, an HRA framework focusing on generic task types (GTTs), cognitive failure modes (CFMs) and performance shaping factors (PSFs), was applied to code 133 incidents in nuclear power plant commissioning. A multidisciplinary expert team comprising HRA, domain, and integrative experts conducted the coding through a structured three-stage process, ensuring reliability and validity. Statistical association tests were conducted to explore the relationships between different PSFs and between PSFs and CFMs along with our interpretations. Regarding PSF inter-associations, a supplementary questionnaire survey was administered to capture the strengths of these associations in general tasks. The combined incident and survey data helped to clarify the origins of the association, including direct causality, mediating effects, confounding effects, and interaction-induced collider effects. Additionally, PSF–CFM associations were used to infer the relative impact of PSFs across different cognitive functions, offering a new approach for validating PSF multipliers in HRA.

Keywords: Human-related incident; Human error; Human reliability analysis; Nuclear power plant (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025003655

DOI: 10.1016/j.ress.2025.111164

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