A fuzzy reasoning and fuzzy-analytical hierarchy process based approach to the process of railway risk information: A railway risk management system

Abstract

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.

An Intelligent Railway Safety Risk Assessment Support System for Railway Operation and Maintenance Analysis

“…[8]. However, the triangular and trapezoidal MFs are the most frequently used in safety risk analysis practice [1][2][3][11][12][13].…”

“…Fuzzy qualitative descriptors are extensions of numerical variables in the sense that they are able to represent the condition of an attribute at a given interval by taking fuzzy sets as their values [1][2][3]. The values obtained in the development of fuzzy qualitative descriptors are considered as fuzzy-measuring attributes of objects, in this case, RLs.…”

“…However, there are serious issues involved in both maintaining this position in reality and sustaining the public perception of railway safety excellence [1][2][3]. The UK railway now finds itself in a situation where actual and perceived safeties are real issues, to be dealt with in a new public culture of rapid change, short-term pressures, and instant communications [4,5].…”

“…Collecting sufficient data on which to base a statistical probability of the failure is a costly and difficult undertaking, and the relevance of data to any particular system, as well as its validity, is often questionable [1,11]. Furthermore, in many situations, the data of probability of failure of a system do not exist and it must be estimated based on the expert knowledge and experience or engineering judgement from similar items.…”

Fuzzy-Bayesian-network-based Safety Risk Analysis in Railway Passenger Transport

“…In fact, many risk-based analysis methods for avoiding casualties and property losses have been developed, including pre-hazard analysis (PHA) (Khakzad et al, 2013;Savage, 2005), fault tree analysis (FTA) (Fink et al, 2014;Johnston, 2000), safety check list (Muttram, 2002), risk matrix analysis and risk probability analysis (Khakzad et al, 2011;An et al, 2011). In particular, The Bayesian network modeling method based on probability statistics is a powerful tool for dealing with the uncertainty and causality of the multiple influencing factors (Holický et al, 2013;Trucco et al, 2008).…”