A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry
In recent years, resilience engineering (RE) has attracted widespread interest from industry as well as academia because it presents a new way of thinking about safety and accident. Although the concept of RE was defined scholarly in various areas, there are only few which specifically focus on how...
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Veröffentlicht in: | Reliability engineering & system safety 2013-11, Vol.119, p.88-94 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In recent years, resilience engineering (RE) has attracted widespread interest from industry as well as academia because it presents a new way of thinking about safety and accident. Although the concept of RE was defined scholarly in various areas, there are only few which specifically focus on how to measure RE. Therefore, there is a gap in assessing resilience by quantitative methods. This research aimed at presenting a new method for quantitative assessment of RE using questionnaire and based on principal component analysis. However, six resilience indicators, i.e., top management commitment, Just culture, learning culture, awareness and opacity, preparedness, and flexibility were chosen, and the data related to those in the 11 units of a process industry using a questionnaire was gathered. The data was analyzed based on principal component analysis (PCA) approach. The analysis also leads to determination of the score of resilience indicators and the process units. The process units were ranked using these scores. Consequently, the prescribed approach can determine the poor indicators and the process units. This is the first study that considers a quantitative assessment in RE area which is conducted through PCA. Implementation of the proposed methods would enable the managers to recognize the current weaknesses and challenges against the resilience of their system.
•We quantitatively measure the potential of resilience.•The results are more tangible to understand and interpret.•The method facilitates comparison of resilience state among various process units.•The method facilitates comparison of units' resilience state with the best practice. |
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ISSN: | 0951-8320 1879-0836 |
DOI: | 10.1016/j.ress.2013.05.003 |