Fuzzy rule-based Fine-Kinney risk assessment approach for rail transportation systems

Rail transportation is one of the most crucial public transportation types for big and crowded cities. In rail transportation systems, stakeholders face serious issues involved in workshops, stations, lines and their environments, and general office buildings. In order to reach an increased awareness and better occupational health and safety (OHS) management, a new risk assessment approach is proposed in this study. This approach includes a combination of Fine-Kinney method and a fuzzy rule-based expert system. It captures nonlinear causal relationships between Fine-Kinney parameters. Since there is a high level of vagueness involved in the OHS risk assessment data, the rule-based expert system is developed for probability (P), exposure (E), and consequence (C) for evaluating risk score. A case study is carried out in a rail transportation system in Istanbul/Turkey, and a comparison with the classical Fine-Kinney method is discussed. Results of the case study reveal risk clusters and corresponding control measures that should be taken into consideration. The study methodologically contributes to risk assessment in the knowledge, while case study in a real rail transportation system offers an insight into public transport industry in safety improvement.