Learning from accidents: analysis of multi-attribute events and implications to improve design and reduce human errors

R. Moura, M. Beer, E. Patelli, J. Lewis, F. Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

High-technology accidents are likely to occur under a complex interaction of multiple active failures and latent conditions, and recent major accidents investigations are increasingly highlighting the role of human error or human-related factors as significant contributors. Latent conditions might have long incubation periods, which implies that a number of design failures may be embedded in systems until human errors trigger an accident sequence. Consequently, there is a need to scrutinise the relationship between enduring design deficiencies and human erroneous actions as a conceivable way to minimise accidents. This study will tackle this complex problem by applying an artificial neural network approach to a proprietary multi-attribute accident dataset, in order to disclose multidimensional relationships between human errors and design failures. Clustering and data mining results are interpreted to offer further insight into the latent conditions embedded in design. Implications to support the development of design failure prevention schemes are then discussed.

Original languageEnglish
Title of host publicationSafety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015
EditorsEnrico Zio, Luca Podofillini, Wolfgang Kröger, Bruno Sudret, Božidar Stojadinović
Pages3049-3056
Number of pages8
Publication statusPublished - 30 Sep 2015
Event25th European Safety and Reliability Conference, ESREL 2015 - Zurich, Swaziland
Duration: 7 Sep 201510 Sep 2015

Publication series

NameSafety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015

Conference

Conference25th European Safety and Reliability Conference, ESREL 2015
CountrySwaziland
CityZurich
Period7/09/1510/09/15

Keywords

  • reliability analysis
  • shaping factors
  • nuclear power plants
  • accidents
  • complex networks
  • neural networks
  • artificial neural network approach

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