No abstract

No abstract

No abstract

This paper describes the application of the Petri Net modelling approach to managing the maintenance process of railway bridges. The Petri Net model accounts for the degradation, inspection and repair processes of individual bridge elements in investigating the effectiveness of alternative maintenance strategies. The times governing the degradation and repair processes considered are stochastic and defined by the appropriate Weibull distribution. The model offers a capability for modelling the bridge asset which overcomes the limitations in the currently used modelling techniques reported in the literature. The bridge model also provides a means of predicting the future asset condition as a result of adopting different maintenance strategies. The solution of the Petri Net model is performed using a Monte Carlo simulation routine. The application of the model to a typical metal railway bridge is also presented in the paper.

A main challenge in railway asset management is selecting the maintenance strategies to apply to each asset on the network in order to effectively manage the railway infrastructure given that some performance and safety targets have to be met under budget constraints. Due to economic, functional and operational dependencies between different assets and different sections of the network, optimal solutions at network level not always include the best strategies available for each asset group. This paper presents a modelling approach to support decisions on how to effectively maintain a railway infrastructure system. For each railway asset, asset state models combining degradation and maintenance are used to assess the impact of any maintenance strategy on the future asset performance. The asset state models inform a network-level optimisation model aimed at selecting the best combination of maintenance strategies to manage each section of a given railway network in order to minimise the impact of the assets conditions on service, given budget constraints and performance targets. The optimisation problem is formulated as an integer-programming model. By varying the model parameters, scenario analysis can be performed so that the infrastructure manager is provided with a range of solutions for different combination of budget available and performance targets.