Risk quantification and analysis of coupled factors based on the DEMATEL model and a bayesian network

Jian Jiao, Mengwei Wei, Yuan Yuan, Tingdi Zhao

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

With the developing of high integrations in large scale systems, such as aircraft and other industrial systems, there are new challenges in safety analysis due to the complexity of the mission process and the more complicated coupling characteristic of multi-factors. Aiming at the evaluation of coupled factors as well as the risk of the mission, this paper proposes a combined technology based on the Decision Making Trial and Evaluation Laboratory (DEMATEL) model and the Bayesian network (BN). After identifying and classifying the risk factors from the perspectives of humans, machines, the environment, and management, the DEMATEL technique is adopted to assess their direct and/or indirect coupling relationships to determine the importance and causality of each factor; moreover, the relationship matrix in the DEMATEL model is used to generate the BN model, including its parameterization. The inverse reasoning theory is then implemented to derive the probability, and the risk of the coupled factors is evaluated by an assessment model integrating the probability and severity. Furthermore, the key risk factors are identified based on the risk radar diagram and the Pareto rule to support the preventive measurements. Finally, an application of the take-off process of aircraft is provided to demonstrate the proposed method.

Original languageEnglish
Article number317
JournalApplied Sciences (Switzerland)
Volume10
Issue number1
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes

Keywords

  • Bayesian network
  • Coupled risk factors
  • DEMATEL
  • Risk assessment
  • Safety

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