Risk Assessment and Loss Estimation for the Rail Industry
Objective:
- To generate a series of cause-consequence Quantitative Risk Assessment (QRA) models to represent risk on the railway for general operations and modernisation work;
- To create a Loss Estimator for railways to undertake a loss analysis assessment to estimate commercial, safety and financial losses for the consequence scenarios generated in the QRA models.
Added value to client:
RM Consultants (RMC) has a broad range of experience in risk assessment and development of quantitative risk models, and has a strong understanding of railway operations and projects. We applied our knowledge of software tools for supporting engineering decisions and safety cases to this work, and provided a proven holistic approach to cost and safety analysis of current operations and investigations into future technologies and operations. This drew on previous work in modelling the physical processes dominant in several industries such as transport, oil and gas and nuclear safety.
Activity:
RMC was contracted to develop and implement modelling techniques for risk based loss estimation as an aid to comparison of modernisation and engineering options on the railway.
This was accomplished by:
- Generating QRA models to provide a uniform basis of comparison of the diverse consequences present in the industry. Identifying core hazards that are representative of the range of hazards associated with railway operations;
- Creating a logical progression of causal events, through hazard and consequence trees and mitigating ‘barriers’ that aid in preventing escalation of an incident to an accident;
- Conducting elicitation workshops with rail network employees to identify any model requirements and limitations;
- Applying the cause-consequence QRA models to the entire rail network, and focusing more specifically on the modernisation operations of the West Coast Main Line;
- Developing a loss estimator for railways which is capable of reacting to the dynamics of the model and predicting realised and non-realised events. The loss estimator uses modelling techniques and data drawn from historical knowledge;
- Modelling the sequence from failure to loss producing scenarios and estimating their frequency. QRA and loss estimators aid in the decision support by establishing tangible losses for each scenario.
The loss estimation approach produces comparable consequences for a range of different financial or safety impacts.
