Application of Bayesian Belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents

2013 ◽  
Vol 110 ◽  
pp. 89-109 ◽  
Author(s):  
Marcelo Ramos Martins ◽  
Marcos Coelho Maturana
2009 ◽  
Author(s):  
Ronald Laurids Boring ◽  
Johanna Oxstrand ◽  
Michael Hildebrandt

Author(s):  
Ronald Boring ◽  
Thomas Ulrich ◽  
Torrey Mortenson ◽  
David German

This paper provides background on the process to enhance human reliability analysis (HRA) for long-duration space applications. While short-duration missions largely mirror ground activities and fit well with existing HRA methods, new missions to the Moon or Mars entail a significantly longer duration of time in space for astronauts. This extended period in space presents opportunities to affect astronaut performance that require consideration of new performance shaping factors (PSFs). In the present paper, we conducted a meta-analysis on fatigue and developed a new PSF to account for chronic sleep deprivation associated with long-duration space missions. Fatigue provides a starting point for additional PSFs needed for space HRA.


2021 ◽  
pp. 106002802199964
Author(s):  
Matthew D. Jones ◽  
Jonathan Clarke ◽  
Calandra Feather ◽  
Bryony Dean Franklin ◽  
Ruchi Sinha ◽  
...  

Background: In a recent human reliability analysis (HRA) of simulated pediatric resuscitations, ineffective retrieval of preparation and administration instructions from online injectable medicines guidelines was a key factor contributing to medication administration errors (MAEs). Objective: The aim of the present study was to use a specific HRA to understand where intravenous medicines guidelines are vulnerable to misinterpretation, focusing on deviations from expected practice ( discrepancies) that contributed to large-magnitude and/or clinically significant MAEs. Methods: Video recordings from the original study were reanalyzed to identify discrepancies in the steps required to find and extract information from the NHS Injectable Medicines Guide (IMG) website. These data were combined with MAE data from the same original study. Results: In total, 44 discrepancies during use of the IMG were observed across 180 medication administrations. Of these discrepancies, 21 (48%) were associated with an MAE, 16 of which (36% of 44 discrepancies) made a major contribution to that error. There were more discrepancies (31 in total, 70%) during the steps required to access the correct drug webpage than there were in the steps required to read this information (13 in total, 30%). Discrepancies when using injectable medicines guidelines made a major contribution to 6 (27%) of 22 clinically significant and 4 (15%) of 27 large-magnitude MAEs. Conclusion and Relevance: Discrepancies during the use of an online injectable medicines guideline were often associated with subsequent MAEs, including those with potentially significant consequences. This highlights the need to test the usability of guidelines before clinical use.


Author(s):  
Yao Wang

According to existing research results, fire risk makes a significant contribution to the total risk of a nuclear power plant (NPP). So fire probabilistic safety analysis (PSA) for NPPs is becoming more and more important in recent years. How to perform human reliability analysis (HRA) which is an essential part of PSA is therefore being paid more and more attention in fire PSA. This paper describes the characteristics and special considerations of HRA in fire PSA, and demonstrates in fire PSA how to use SPAR-H method which is so-called an advanced second-generation HRA method and is being widely used in PSA for Chinese NPPs. The study results can be a reference for other HRA analysts to use SPAR-H method in fire PSA models or other PSA models in Chinese NPPs or the world-wide nuclear industry.


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