Embedded within modern technological systems, human error is the largest, and indeed dominant contributor to accident cause. The consequences dominate the risk profiles for nuclear power and for many other technologies. We need to quantify the probability of human error for the system as an integral contribution within the overall system failure, as it is generally not separable or predictable for actual events. We also need to provide a means to manage and effectively reduce the failure (error) rate. The fact that humans learn from their mistakes allows a new determination of the dynamic probability and human failure (error) rate in technological systems. The result is consistent with and derived from the available world data for modern technological systems. Comparisons are made to actual data from large technological systems and recent catastrophes. Best estimate values and relationships can be derived for both the human error rate, and for the probability. We describe the potential for new approaches to the management of human error and safety indicators, based on the principles of error state exclusion and of the systematic effect of learning.
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12th International Conference on Nuclear Engineering
April 25–29, 2004
Arlington, Virginia, USA
Conference Sponsors:
- Nuclear Engineering Division
ISBN:
0-7918-4689-X
PROCEEDINGS PAPER
The Probability and Management of Human Error
Romney D. Duffey,
Romney D. Duffey
Atomic Energy of Canada, Ltd., Chalk River, ON, Canada
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John W. Saull
John W. Saull
International Federation of Airworthiness, W. Sussex, UK
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Romney D. Duffey
Atomic Energy of Canada, Ltd., Chalk River, ON, Canada
John W. Saull
International Federation of Airworthiness, W. Sussex, UK
Paper No:
ICONE12-49287, pp. 133-137; 5 pages
Published Online:
November 17, 2008
Citation
Duffey, RD, & Saull, JW. "The Probability and Management of Human Error." Proceedings of the 12th International Conference on Nuclear Engineering. 12th International Conference on Nuclear Engineering, Volume 3. Arlington, Virginia, USA. April 25–29, 2004. pp. 133-137. ASME. https://doi.org/10.1115/ICONE12-49287
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