Risk Assessment of Critical Infrastructure Based on Information Uncertainty

• Main Authors: Yen-Wen,Yeh, 葉彥彣
• Other Authors: 劉建浩
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/nwds87

碩士 === 國立臺北科技大學 === 工業工程與管理系碩士班 === 105 === Critical infrastructure is an important asset of the state and is the basic function and service of the peoples daily life, which provided by the state to maintain peoples livelihood, economy and government operation. The disruption of infrastructure will affect the public service, peoples life as well as national security. Therefore, to further develop and improve critical infrastructure and disaster preventive measures, research must be continued. In this study, an integrated risk assessment model that combines Failure Mode and Effect analysis (FMEA) and Multiple Attribute Decision analysis (MADM) is proposed. First, by summarizing the important risk factors that may affect the critical infrastructure, and establish the risk model of potential failure. The importance of the severity, occurrence and detectability is established through Analytic Hierarchy process, AHP. By pairwise comparing the risk rating indexes, the weight of each risk rating index can be obtained. Finally, VIKOR is used to calculate the risk priority number (RPN) that may contribute to the critical infrastructure and rank the risk factors accordingly. The RPN will help us find out the most essential factor to the failure and allow us to follow up with adjustment and improvement, so as to reduce the effects caused by the disaster. In order to overcome the uncertainty of the experts’ opinions due to incomplete information or their subjective preferences, fuzzy theory is used to in the proposed model to reflect the real problem situation. In this paper, we have selected Turbine Generator Plant as the main study of our research. The main component of the Turbine Generator Plant is the Steam Turbine. While a Steam Turbine can be durable, probability of the breaking down is not negligible. Therefore, we adopt the FMEA risk indicator which consider the following factors such as severity of the fault, probability of occurrence, degree of detection and also the cost of prevention as assessment of the quality of the main power generation equipment. Analysis made using the AHP method show that majority of the experts considers that the severity of the fault of the main power equipment as the most important factor for the failure of the power plant model. Thus, the severity of the fault of the main power supply equipment should be the most crucial consideration to have a successful model. Steam turbine are also bound to have faults where a total of twenty factors are taken into considerations. With the VIKOR method, the risk priorities are “servo valve failure” as the most important factor followed by “main turbine with high vibration”, “main turbine bearing metal with high temperature”, “foreign objective damage”, “bearing loose, deformation and damage”. Finally, this study provided some suggestions for prevention and evaluated the top 5 risk factors in order to achieve the best improving strategy.