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Journal Articles Safety Science Year : 2016

Emergency response plan: Model-based assessment with multi-state degradation


Local Emergency Response Plans (LERP) must be assessed before being triggered, to ensure proper execution of missions in a crisis situation. However, there is very little research on plan assessment methods. Plan assessment has traditionally involved consideration of only two states: complete functioning, or failure. In this paper, we propose an LERP assessment method that evaluates LERP performance under multiple states of its resource degradation. Our method relies on Function-Interaction-Structure (FIS) modeling to describe interaction between resource degradation and plan failure. Our multi-state and model-based approach allows a comprehensive analysis of LERP weak points, and provides the framework for evaluating a wide range of engaged resources. Consideration of multiple states of resource degradation is needed in order to show to what extent an LERP is required. We propose to combine a Fault-Tree embedded in FIS with a Multi-State System approach. With this approach, plan evaluators can study LERP effectiveness at various levels of incomplete functioning, and can analyze the risk of resource degradation leading to functional impairment of LERP missions. The Multi-State System approach provides knowledge about the likelihood of an LERP being in multiple states of degradation on disaster day. Input data for the analysis are gathered using developed questionnaires. These are used by Emergency Response Plan makers to evaluate the probability of resource degradation states, and to develop strategies to increase the likelihood of LERP success. This paper shows how the proposed methodology, based on modeling and Multi-Level Fault-Trees, can inform the analysis of an LERP evacuation function.
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Dates and versions

emse-01233697 , version 1 (25-11-2015)



Clément Girard, Pierre David, Eric Piatyszek, Jean-Marie Flaus. Emergency response plan: Model-based assessment with multi-state degradation. Safety Science, 2016, 85, pp.230-240. ⟨10.1016/j.ssci.2015.12.016⟩. ⟨emse-01233697⟩
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