Risk Scenario Generation Based on Importance Measure Analysis

Xing Pan, Lunhu Hu, Ziling Xin, Shenghan Zhou, Yanmei Lin and Yong Wu
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Xing Pan: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China
Lunhu Hu: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China
Ziling Xin: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China
Shenghan Zhou: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China
Yanmei Lin: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China
Yong Wu: School of Reliability & Systems Engineering, Beihang University, Beijing 100191, China

Sustainability, 2018, vol. 10, issue 9, 1-18

Abstract: A risk scenario is a combination of risk events that may result in system failure. Risk scenario analysis is an important part of system risk assessment and avoidance. In engineering activity-based systems, important risk scenarios are related to important events. Critical activities, meanwhile, mean risk events that may result in system failure. This article proposes these definitions of risk event and risk scenario based on the characteristics of risk in engineering activity-based systems. Under the proposed definitions, a risk scenario framework generated based on importance measure analysis is given, in which critical activities analysis, risk event identification, and risk scenario generation are the three main parts. Important risk events are identified according to activities’ uncertain importance measure and important risk scenarios are generated on the basis of a system’s critical activities analysis. In the risk scenario generation process based on importance analysis, the importance degrees of network activities are ranked to identify the subject of risk events, so that risk scenarios can be combined and generated by risk events and the importance of scenarios is analyzed. Critical activities are analyzed by Taguchi tolerance design, mathematical analysis, and Monte Carlo simulation methods. Then the degrees of uncertain importance measure of activities are solved by the three methods and these results are compared. The comparison results in the example show that the proposed method of uncertain importance measure is very effective for distinguishing the importance level of activities in systems. The calculation and simulation results also verify that the risk events composed of critical activities can generate risk scenarios.

Keywords: risk scenario; importance measure; uncertain importance measure; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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