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URN: urn:nbn:de:0030-drops-37406
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Improving Safety-Critical Systems by Visual Analysis

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Abstract

The importance analysis provides a means of analyzing the contribution of potential low-level system failures to identify and assess vulnerabilities of safety-critical systems. Common approaches attempt to enhance the system safety by addressing vulnerabilities using an iterative analysis process, while considering relevant constraints, e.g., cost, for optimizing the improvements. Typically, data regarding the analysis process is presented across several views with few interactive associations among them. Consequently, this hampers the identification of meaningful information supporting the decision making process. In this paper, we propose a visualization system that visually supports engineers in identifying proper solutions. The visualization integrates a decision tree with a plot representing the cause-effect relationship between the improvement ideas of vulnerabilities and the resulting risk reduction of system. Associating a component fault tree view with the plot allows to maintain helpful context information. The introduced visualization approach enables system and safety engineers to identify and analyze optimal solutions facilitating the improvement of the overall system safety.

BibTeX - Entry

@InProceedings{yang_et_al:OASIcs:2012:3740,
  author =	{Yi Yang and Patric Keller and Yarden Livnat and Peter Liggesmeyer},
  title =	{{Improving Safety-Critical Systems by Visual Analysis}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{43--58},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Christoph Garth and Ariane Middel and Hans Hagen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2012/3740},
  URN =		{urn:nbn:de:0030-drops-37406},
  doi =		{http://dx.doi.org/10.4230/OASIcs.VLUDS.2011.43},
  annote =	{Keywords: fault tree analysis, importance and sensitivity analysis, information vi- sualization, decision tree, safety analysis}
}

Keywords: fault tree analysis, importance and sensitivity analysis, information vi- sualization, decision tree, safety analysis
Seminar: Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011
Issue date: 2012
Date of publication: 2012


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