Cost Effective Predictive Railway Track Maintenance

Efficient railway track maintenance is crucial due to the increasing demand for rail transportation. Reducing costs by optimizing maintenance procedures and operations is essential, and predictive maintenance approaches are necessary to achieve this. We summarized previous literature on track geometry and developed a predictive model for maintenance cost management. We test random forest and SVM predictions on a simulated dataset This information can assist railway companies in improving maintenance practices, planning costs, and enhancing network performance and efficiency.