An extended CREAM model based on analytic network process under the type‐2 fuzzy environment for human reliability analysis in the high‐speed train operation

2020 ◽  
Author(s):  
Xiaoqing Chen ◽  
Xinwang Liu ◽  
Yong Qin
Keyword(s):  
Reliability Analysis ◽  
High Speed ◽  
Analytic Network Process ◽  
High Speed Train ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Fuzzy Environment ◽  
Network Process ◽  
Train Operation

Human reliability analysis for control room upgrades

2009 ◽  
Author(s):  
Ronald Laurids Boring ◽  
Johanna Oxstrand ◽  
Michael Hildebrandt
Keyword(s):  
Reliability Analysis ◽  
Control Room ◽  
Human Reliability ◽  
Human Reliability Analysis

Fatigue As A Performance Shaping Factor In Human Reliability Analysis For Long-Duration Spaceflight

2020 ◽  
Vol 64 (1) ◽  
pp. 1681-1685
Author(s):  
Ronald Boring ◽  
Thomas Ulrich ◽  
Torrey Mortenson ◽  
David German
Keyword(s):  
Reliability Analysis ◽  
Meta Analysis ◽  
Extended Period ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Space Applications ◽  
Performance Shaping Factors ◽  
Long Duration ◽  
Starting Point ◽  
Chronic Sleep

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.

scholarly journals Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis

2021 ◽  
pp. 106002802199964
Author(s):  
Matthew D. Jones ◽  
Jonathan Clarke ◽  
Calandra Feather ◽  
Bryony Dean Franklin ◽  
Ruchi Sinha ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Medication Administration ◽  
Original Study ◽  
Human Reliability ◽  
Large Magnitude ◽  
Human Reliability Analysis ◽  
Video Recordings ◽  
Medication Administration Errors ◽  
Key Factor ◽  
Clinically Significant

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.

The Human Reliability Analysis in Fire PSA Using Spar-H Method

2013 ◽  
Author(s):  
Yao Wang
Keyword(s):  
Reliability Analysis ◽  
Nuclear Power ◽  
Significant Contribution ◽  
Fire Risk ◽  
Nuclear Industry ◽  
Total Risk ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Study Results ◽  
In Fire

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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