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Value of analyzing operating events

  • R. Youngblood
  • , G. Maggio
  • , C. Everett
  • , A. Hall

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

If one had no uncertainty regarding scenarios, frequencies, or consequences associated with a hazardous operation, then from a simplistic quantitative point of view, there would be nothing more to be learned by analyzing operating experience. However, this is not generally the case; several kinds of reasons can be offered for analyzing operating experience in the context of risk management. Even if the scenario set is complete, there may be uncertainty regarding the level of performance at a facility (whether its programs are suitably maintaining equipment reliability). Alternatively, even if performance is satisfactory, there may be risk contributors that are significant but not modelled, or modelled inadequately. Although some catastrophic events may occur with no operational precursors, in other cases, the potential for certain risk contributions may be revealed by analysis of experience. Methods for extracting insights of this kind from analysis of operating experience are still evolving, especially the problem of deciding which events to focus on. The paper will examine the usefulness of measures of "surprise" in this regard.

Original languageEnglish
Title of host publication9th International Conference on Probabilistic Safety Assessment and Management 2008, PSAM 2008
Pages2610-2617
Number of pages8
StatePublished - 2008
Event9th International Conference on Probabilistic Safety Assessment and Management 2008, PSAM 2008 - Hong Kong, China
Duration: May 18 2008May 23 2008

Publication series

Name9th International Conference on Probabilistic Safety Assessment and Management 2008, PSAM 2008
Volume4

Conference

Conference9th International Conference on Probabilistic Safety Assessment and Management 2008, PSAM 2008
Country/TerritoryChina
CityHong Kong
Period05/18/0805/23/08

Keywords

  • Operating events analysis
  • Performance indicators
  • Precursor analysis
  • Surprise

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