A fuzzy reasoning based approach to qualitative railway risk assessment

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.