Phoenix – A model-based Human Reliability Analysis methodology: Qualitative Analysis Procedure-Reference-Cited by-同舟云学术

Phoenix – A model-based Human Reliability Analysis methodology: Qualitative Analysis Procedure

Published:2016-01 Issue: Volume:145 Page:301-315
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Ekanem Nsimah J.,Mosleh Ali,Shen Song-Hua

Funder

U.S. Nuclear Regulatory Commission (USNRC)

Center for Risk and Reliability of the University of Maryland

USNRC

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference38 articles.

1. Handbook of human reliability analysis with emphasis on nuclear power plant applications;Swain,1983

2. Williams J. "HEART: A proposed method for assessing and reducing human error,"Advances in Reliability Technology Symposium (9th), University of Bradford 1986.

3. SLIM-MAUD: an approach to assessing human error probabilities using structured expert judgment;Embrey,1984

4. Cognitive reliability and error analysis method (CREAM);Hollnagel,1998

5. The SPAR-H human reliability analysis method;Gertman,2005

Cited by 90 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Mirror the mind of crew: Maritime risk analysis with explicit cognitive processes in a human digital twin;Advanced Engineering Informatics;2024-10

2. Advanced Human Reliability Analysis Approach for Ship Convoy Operations via a Model of IDAC and DBN: A Case from Ice-Covered Waters;Journal of Marine Science and Engineering;2024-09-03

3. Dynamic human error risk assessment of group decision-making in extreme cooperative scenario;Reliability Engineering & System Safety;2024-09

4. Phoenix–A model-based human reliability analysis methodology: Data sources and quantitative analysis procedure;Reliability Engineering & System Safety;2024-08

5. A data-driven Bayesian network of management and organizational factors for human reliability analysis in the process industry;Heliyon;2024-08