Railway Safety Management is a complex subject that involves a significant amount of manual intervention in the assessment, analysis and control of risk. Supporting documentation is usually worked on by multiple parties, with differences in system viewpoints and writing styles. Maintaining quality safety documentation is therefore an interesting challenge for the industry.
This tool assesses the ‘quality’ of a risk log in either ‘real time’ or at regular intervals to check the output from critical risk workshop sessions. It uses Natural Language Processing and Machine Learning to assess the quality of a hazard log based solely on its textual content. The tool has been built around CENELC standards to aid compliance with both standards and risk management best practice. It has been developed in collaboration with Lancaster University.