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a b s t r a c tRisk management is becoming increasingly important for railway companies in order to safeguard their passengers and employees while improving safety and reducing maintenance costs. However, in many circumstances, the application of probabilistic risk analysis tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents the development of a risk management system for railway risk analysis using fuzzy reasoning approach and fuzzy analytical hierarchy decision making process. In the system, fuzzy reasoning approach (FRA) is employed to estimate the risk level of each hazardous event in terms of failure frequency, consequence severity and consequence probability. This allows imprecision or approximate information in the risk analysis process. Fuzzy analytical hierarchy process (fuzzy-AHP) technique is then incorporated into the risk model to use its advantage in determining the relative importance of the risk contributions so that the risk assessment can be progressed from hazardous event level to hazard group level and finally to railway system level. This risk assessment system can evaluate both qualitative and quantitative risk data and information associated with a railway system effectively and efficiently, which will provide railway risk analysts, managers and engineers with a method and tool to improve their safety management of railway systems and set safety standards. A case study on risk assessment of shunting at Hammersmith depot is used to illustrate the application of the proposed risk assessment system.

This article presents the development of a fuzzy-reasoning-based railway risk assessment system. The proposed method can evaluate qualitative and quantitative risk data in a uniform manner for railway risk assessment. It permits risk analysts to assess the risks associated with the failure modes directly using linguistic terms. The proposed railway risk assessment system is capable of assessing the risks at component level, subsystem level, and system level. The outcomes of the risk assessment are represented in two formats, risk score and risk category with a belief of percentage, which provide very useful risk information to railway designers, operators, engineers, and maintainers. A case study on rolling stock asset risk assessment is used to demonstrate the proposed railway risk assessment system. The results indicate that by using this system, risks associated with a railway system can be assessed effectively and efficiently.

Railway safety is a very complicated subject, which is determined by numerous aspects including human error. Many of the railway risk assessment techniques currently used are comparatively mature tools. However, in many circumstances, the application of these tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents a risk assessment methodology for conducting systematic risk assessment using fuzzy reasoning approach and fuzzy analytical hierarchy decision-making process. In this method, qualitative descriptors are employed to describe frequency of occurrence, consequence severity, weight factor, and risk level. The proposed risk assessment method can evaluate both qualitative and quantitative risk data, and information associated with railway operation efficiently and effectively. The outcomes of risk assessment are represented as the risk degrees and the defined risk categories of risk levels (RLs) with a belief of percentage, which provide very useful risk information to decision makers. This will provide railway risk analysts, managers, and engineers with a method and tool to improve their safety management and set safety standards. A case study of risk assessment of shunting at Waterloo depot is used to illustrate the application of the proposed methodology. by railway maintenance work in the past ten years, brought about through either a major injury or an injury that rendered them unable to work for over three days. This shows the dangerous nature of the railway industry and demonstrates the need for increased awareness and better safety management [2, 4, 7]. Many accidents and incidents occurred in the railway depots over the years, demanding improvement in safety management. To assess how this can be effectively achieved, knowledge on the nature and causes of these accidents is fundamental. Therefore, risk analysis plays a central role in the railway safety and health management framework. The most common hazards in the railway depots identified by the railway industry over the years [2-4, 6, 8-10] provide very useful information for risk analysis, for example, derailment hazards, collision hazards, fire hazards, electrocution hazards, falls hazards, train strike hazards, slip/trip hazards, platform train interface JRRT106

Network-based probability analysis of train derailments caused by various extreme weather patterns on railway turnouts', Safety Science.

Resource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. In this method, the project portfolio resource risk factors are first identified by taking project interdependency into consideration, and then the Bayesian network model is developed to analyze the risk level of the identified risk factors in which expert judgments and fuzzy set theory are integrated to determine the probabilities of all risk factors to deal with incomplete risk data and information. To reduce the subjectivity of expert judgments, the expert weights are determined by combining experts’ background and reliability degree of expert judgments. A numerical analysis is used to demonstrate the application of the proposed methodology. The results show that project portfolio resource risks can be analyzed effectively and efficiently. Furthermore, “poor communication and cooperation among projects,” “capital difficulty,” and “lack of sharing technology among projects” are considered the leading factors of the project portfolio resource risk. Risk-reduction strategic decisions based on the results of risk assessment can be made, which provide project managers with a useful method or tool to manage project risks.

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Abstract:The paper presents the development of an intelligent railway safety risk assessment based support system. The proposed method can evaluate qualitative and quantitative safety risk data and information in a uniform manner for railway safety risk assessment. It permits the safety risk analysts to assess the risks associated with the failure modes directly using linguistic terms, i.e. qualitative descriptors. The proposed intelligent railway safety risk assessment system is capable of assessing the risks at component level, sub-system level and system level. It can assess not only "hard" risks (e.g. risks of a system), but also "soft" risks (e.g. staff risks). The outcomes of safety risk assessment are represented in two formats, risk score and risk category with a belief of percentage, which provide very useful safety risk information to railway designers, operators, engineers and maintainers for risk response decision making. An illustrative example of staff risk assessment in a railway depot is used to demonstrate the proposed intelligent railway safety risk assessment system. The results indicate that by using the proposed system, risks associated with a railway depot can be assessed effectively and efficiently.