KRAIL: A knowledge-driven framework for human reliability analysis integrating IDHEAS-DATA and large language models
Xingyu Xiao,
Peng Chen,
Ben Qi,
Hongru Zhao,
Jingang Liang,
Jiejuan Tong and
Haitao Wang
Reliability Engineering and System Safety, 2026, vol. 265, issue PB
Abstract:
Human reliability analysis (HRA) is crucial for evaluating and improving the safety of complex systems. Recent efforts have focused on estimating human error probability (HEP), but existing methods often rely heavily on expert knowledge, which can be subjective and time-consuming. Inspired by the success of large language models (LLMs) in natural language processing, this paper introduces KRAIL, a novel two-stage framework for knowledge-driven reliability analysis, integrating IDHEAS-DATA, knowledge graph and LLMs. The knowledge graph serves as a retrieval-augmented generation (RAG) layer that swiftly surfaces context-relevant evidence, while an expert-in-the-loop validation step alleviates data sparsity and curbs LLM hallucinations. Comprehensive experiments on authoritative HRA benchmark datasets show that KRAIL produces more accurate HEP estimates than state-of-the-art methods, even under partial-information conditions, while completing end-to-end assessments in under 150 s. These results underscore KRAIL’s potential to enable fast, transparent, and scalable human-error quantification for risk-informed decision making.
Keywords: Human reliability analysis (HRA); Retrieval-augmented generation (RAG); Knowledge graph; Large language models (LLMs) (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832025007859
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:265:y:2026:i:pb:s0951832025007859
DOI: 10.1016/j.ress.2025.111585
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().