System-wide assessment of intervention strategies for railway infrastructure

Rama, Dovile; Andrews, John D.

Abstract

The existing railway infrastructure exhibits faster degradation rates and requires more maintenance effort as a result of increased utilisation. At the same time, due to increased numbers of freight and commuter trains obtaining access to the railway infrastructure to carry out maintenance and repairs, not to mention major enhancements, is becoming more problematic. Furthermore, safety measures put in place in the event of infrastructure faults or delayed completion of intervention activities will cause greater disruptions to train services in the parts of the network with intense train traffic. Taking a system wide view is, therefore, vital for developing efficient intervention strategies that could deliver the desired infrastructure outputs. In this paper we propose a modelling approach for simulation and analysis of railway track asset management strategies integrating different elements of the whole railway system. The approach uses a Petri net modelling technique to construct the railway system model. The model is built in a hierarchical, modular fashion, meaning that the system can be represented at any level of granularity and complexity, ranging from a single-asset system in a small segment of the network to a complex multi-asset system in a large geographical region. The impact of different asset management strategies on the infrastructure functionality and the operation of train services is assessed using the Monte Carlo simulation technique.

Citation

Rama, D., & Andrews, J. D. (2014). System-wide assessment of intervention strategies for railway infrastructure.

• Conference Name: 8th International Conference on Modelling in Industrial Maintenance and Reliability (MIMAR)
• End Date: Jul 12, 2014
• Acceptance Date: Feb 20, 2014
• Publication Date: Jul 12, 2014
• Deposit Date: Dec 16, 2016
• Publicly Available Date: Dec 16, 2016
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/732696
• Contract Date: Dec 16, 2016