We show a new way to track and measure safety and performance using learning curves derived on a mathematical basis. When unusual or abnormal events occur in plants and equipment, the regulator and good management practice requires they be reported, investigated, understood and rectified. In addition to reporting so-called “significant events”, both management and the regulator often set targets for individual and collective performance, which are used for both reward and criticism. For almost completely safe systems, like nuclear power plants, commercial aircraft and chemical facilities, many parameters are tracked and measured. Continuous improvement has to be demonstrated, as well as meeting reduced occurrence rates, which are set as management goals or targets. This process usually takes the form of statistics for availability of plant and equipment, forced or unplanned maintenance outage, loss of safety function, safety or procedural violations, etc. These are often rolled up into a set of so-called “Performance Indicators” as measures of how well safety and operation is being managed at a given facility. The overall operating standards of an industry are also measured. A whole discipline is formed of tracking, measuring, reporting, managing and understanding the plethora of indicators and data. Decreasing occurrence rates and meeting or exceeding goals are seen and rewarded as virtues. Managers and operators need to know how good is their safety management system that has been adopted and used (and paid for), and whether it can itself be improved. We show the importance of accumulated experience in correctly measuring and tracking the decreasing event and error rates speculating a finite minimum rate. We show that the rate of improvement constitutes a measurable “learning curve”, and the attainment of the goals and targets can be affected by the adopted measures. We examine some of the available data on significant events, reportable occurrences, and loss of availability. We suggest the use of learning curves as a means of accurately tracking progress; and stress the importance of a sustained learning environment in performance improvement.
Skip Nav Destination
10th International Conference on Nuclear Engineering
April 14–18, 2002
Arlington, Virginia, USA
Conference Sponsors:
- Nuclear Engineering Division
ISBN:
0-7918-3596-0
PROCEEDINGS PAPER
How Good Is Good: Improved Tracking and Managing of Safety Goals, Performance Indicators, Production Targets and Significant Events Using Learning Curves
Romney B. Duffey,
Romney B. Duffey
Atomic Energy of Canada, Ltd., Chalk River, ON, Canada
Search for other works by this author on:
John W. Saull
John W. Saull
International Federaton of Airworthiness, East Grinstead, West Sussex, UK
Search for other works by this author on:
Romney B. Duffey
Atomic Energy of Canada, Ltd., Chalk River, ON, Canada
John W. Saull
International Federaton of Airworthiness, East Grinstead, West Sussex, UK
Paper No:
ICONE10-22426, pp. 271-280; 10 pages
Published Online:
March 4, 2009
Citation
Duffey, RB, & Saull, JW. "How Good Is Good: Improved Tracking and Managing of Safety Goals, Performance Indicators, Production Targets and Significant Events Using Learning Curves." Proceedings of the 10th International Conference on Nuclear Engineering. 10th International Conference on Nuclear Engineering, Volume 2. Arlington, Virginia, USA. April 14–18, 2002. pp. 271-280. ASME. https://doi.org/10.1115/ICONE10-22426
Download citation file:
7
Views
Related Proceedings Papers
Related Articles
Developing and Implementing Artificial Intelligence-Based Classifier for Requirements Engineering
ASME J of Nuclear Rad Sci (October,2021)
Reliability of Steam Generator Tubes With Axial Cracks
J. Pressure Vessel Technol (November,1996)
Plant Life Management Models: A Comparison With Analysis of Impact on Both Safety and Nonsafety Issues
J. Pressure Vessel Technol (June,2011)
Related Chapters
Introduction
Computer Vision for Structural Dynamics and Health Monitoring
Use of PSA in Lisencing of EPR 1600 in Finland (PSAM-0160)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
Introduction
Pipe Stress Engineering