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Looking for errors of omission and commission or The Hunting of the Snark revisited
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, CSELAB - Cognitive Systems Engineering Laboratory.
2000 (English)In: Reliability Engineering & System Safety, ISSN 0951-8320, Vol. 68, no 2, 135-145 p.Article in journal (Refereed) Published
Abstract [en]

Since the early 1990s, considerable effort has been spent to understand what is meant by an `error of commission' (EOC), to complement the traditional notion of an `error of omission' (EOO). This paper argues that the EOO-EOC dyad, as an artefact of the PSA event tree, is insufficient for human reliability analysis (HRA) for several reasons: (1) EOO-EOC fail to distinguish between manifestation and cause, (2) EOO-EOC refer to classes of incorrect actions rather than to specific instances: (3) there is no unique way of classifying an event using EOO-EOC, (4) the set of error modes that cannot reasonably be classified as EOO is too diverse to fit into any single category of its own. Since the use of EOO-EOC leads to serious problems for HRA. an alternative is required. This can be found in the concept of error modes, which has a long history in risk analysis. A specific system for error mode prediction was tested in a simulator experiment. The analysis of the results showed that error modes could be qualitatively predicted with sufficient accuracy (68% correct) to propose this method as a way to determine how operator actions can fail in PSA-cum-HRA. Although this still leaves the thorny issue of quantification, a consistent prediction of error modes provides a better starting point for determining probabilities than the EOO-EOC dyad. It also opens a possibility for quantification methods where the influence of the common performance conditions is prior to and more important than individual failure rates.

Place, publisher, year, edition, pages
2000. Vol. 68, no 2, 135-145 p.
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-47658DOI: 10.1016/S0951-8320(00)00004-1OAI: diva2:268554
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2011-01-14

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Hollnagel, Erik
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The Institute of TechnologyCSELAB - Cognitive Systems Engineering Laboratory
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