Human Reliability and RAMS Management

2018 ◽  
pp. 571-586
Author(s):  
Malcolm Terry Guy Harris
Keyword(s):  
2009 ◽  
Author(s):  
Ronald Laurids Boring ◽  
Johanna Oxstrand ◽  
Michael Hildebrandt

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.


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.


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