From data-based condition analysis to sophisticated asset management for railway tracks

Today, track engineers face increasing cost pressure and strict budget restrictions. This leads to growing difficulty in legitimizing crucial maintenance and renewal measures. Hence, infrastructure managers must spend the available budgets as sustainable and efficient as possible. These boundary conditions require an objective tool enabling both, a component-specific condition evaluation and a preventive maintenance and renewal planning. The present research introduces such a tool for railway track based on innovative track data analyses. Based on the condition evaluation, regression models are applied to predict the quality behaviour in the future. These technical investigations are combined with economical and operational considerations to plan reasonable maintenance lengths for different components in the next years. In a next step, economic evaluations by means of annuity monitoring are executed to find the ideal point in time for the reinvestment of a track section. This information enables to decide whether a necessary measure should be carried out as a maintenance task or if the renewal of the section is the wiser decision. This methodology also allows for calculating an economic damage by neglecting the ideal point in time for reinvestment. Based on this economic damage, it is possible to rank projects in case of insufficient budgets and to spend the available money in the most reasonable way.