This research was devoted to optimising opportunistic tamping scheduling to present a cost-effective approach that considers both preventive and corrective tamping activities. To achieve this, we formulated the track geometry tamping scheduling problem as a mixed integer linear programming model and employed a genetic algorithm for its resolution. Key track quality indicators, including the standard deviation of the longitudinal level and single defects, were considered.We developed predictive models for the evolution of standard deviation and single defects over time, which were utilised to schedule preventive tamping activities and anticipate potential corrective actions. Additionally, we investigated the impact of both preventive and corrective tamping activities on the values of standard deviation and single defects.A case study on data from the Main Western Line in Sweden demonstrated that the fixed cost of occupying each maintenance window significantly influenced the total tamping cost. Moreover, the maintenance cycle interval notably affected the number of required corrective tamping activities. Specifically, a 3-month interval led to over 50 % fewer corrective tamping activities when compared to a 9-month interval. The results revealed that a 6-month interval achieved a favourable balance between corrective and preventive tamping activities and the total cost in our case study.

This paper presents an in-depth case study of a heavy-haul railway line in Sweden to analyze the twist and longitudinal level geometry defects. A linear model was applied to model the evolution of the amplitude of the longitudinal level defects and twist over time. Despite the effect of the defect shapes on the dynamic track loads, the amplitude of the defects still is the only criterion used for the assessment of geometry defect severity. The application of first- and second-order derivatives to capture information about the shape of defects was investigated in the case study. In addition, the RUSBoost algorithm was used to classify track sections into healthy and unhealthy sections using the imbalance class data set. In this algorithm, the standard deviation and the kurtosis of the geometry parameters were used as explanatory variables. Finally, the abnormal track geometry degradation patterns identified in the case study were explored in detail. The results of the analysis can be used directly in maintenance modeling and used for the purpose of maintenance scheduling. 

To predict the occurrence of geometry defects and to achieve a reliable maintenance strategy, accurate positioning of track geometry measurements is of great importance. This paper aims to reduce the positional errors in track geometry measurements by finding an efficient alignment method. Therefore, five alignment methods, i.e. the cross-correlation function, recursive alignment by fast Fourier transform, dynamic time warping, correlation optimized warping, and a combined method, were evaluated and compared concerning their ability to align the measurements precisely, keep the original shape of the measurements, and minimise the use of time and memory. Furthermore, the influence of choosing a proper reference dataset was investigated. A case study based on track geometry data from the Main Western Line in Sweden was conducted to implement and assess the methods. Findings revealed that the combined method could decrease the positional errors of single defects to below 0.25 m in 90% of the trials.

The measurement and improvement of track quality are key issues in determining both the restoration time and cost of railway maintenance. Applying the optimal tamping strategy helps reduce maintenance costs, making operations more cost effective and leading to increased safety and passenger comfort. In this paper, track geometry data from the iron ore line (Malmbanan) in northern Sweden, which handles both passenger and freight trains, are used to evaluate track geometry maintenance in cold climate. The paper describes Trafikverket’s (Swedish Transport Administration) tamping strategy and evaluates its effectiveness in measuring, reporting, and improving track quality. Finally, it evaluates the performance of the maintenance contractor and discusses the importance of the functional requirements stated in the outsourcing contracts.

Turnouts are critical units in railway systems, as they perform the switching procedure that guides trains along different routes. Obtaining measurements of the dynamic behaviour of turnouts under different load conditions helps to improve their design and develop better maintenance strategies. This paper presents two wayside monitoring methods for measuring low frequency vertical displacements of rails affected by train passage; it tests these methods in a case study of the Iron ore line (Malmbanan) in northern Sweden. Rail displacements were measured with two wayside monitoring systems, not the more common inertia system on a track recording car used by the Swedish infrastructure maintenance contractors. The first wayside monitoring method used a laser based sensor to measure the displacements of the rail relative to a measurement rig. It also had a second laser based displacement sensor and an accelerometer to detect any movement of the measurement rig. The second wayside monitoring method, a water pillar system, measured track displacements by measuring the water level of a pipe mounted on the track connected to a cistern placed outside the embankment. This system created a reference position outside the embankment of the turnout, unaffected by passing trains. From the measurements, the rail displacement could be determined for a passing passenger train; viscoelastic behaviour of the track could also be detected, which cannot be done using a regular track recording car.

Switches and crossings (S&Cs) are one of the most critical components of railway track systems in terms of safety, operation and maintenance. Each year, a considerable part of the maintenance budget is spent on inspection, maintenance and renewal of S&Cs. However, applying a cost-effective maintenance strategy helps to achieve the best performance at the lowest possible cost. In Sweden, the geometry of S&Cs is inspected at pre-defined time intervals by the STRIX track measurement car. In this paper, time series for the measured longitudinal level of S&Cs on the Iron Ore Line (Malmbanan) in northern Sweden have been used. Two parameters have been defined in this study, namely the absolute residual area (ARa) and the maximum settlement (Smax), to analyse the geometrical degradation of switches and crossings due to dynamic forces generated from train traffic. The paper also evaluates the growth rate of the longitudinal level degradation as a function of million gross tonnes (MGT). The results facilitate correct decision making in the maintenance process through understanding the degradation rate and defining the optimal maintenance thresholds for the planning process. In the long run this will lead to a cost-effective maintenance strategy with optimized inspection and maintenance intervals.

PurposeSwitches and crossings (S&Cs) are an important component of Banverket's (the Swedish National Rail Administration's) infrastructure and are associated with 13 per cent of the total maintenance cost. Therefore, it is important that a detailed study of different aspects of the costs of S&Cs should be undertaken to analyze individual maintenance costs. This will in the future give the possibility of enhancing the management of infrastructure. Design/methodology/approachA case study is undertaken to study, identify and classify the costs of S&Cs for Banverket. Data are taken from Banverket's maintenance information systems and accounting system. Findings A rough estimation of the cost for individual S&Cs can be identified in this way. The cost varies very much and a more detailed study is needed to validate the cost on this level. The average cost of a group of S&Cs varies less and is therefore more likely to reflect the true cost. The cost varies depending on the amount and type of traffic. Moreover, the type of S&C seems to reflect the cost variation, but further investigation is needed to verify this conclusion. Research limitations/implications The accounting system does not store data for individual assets, and further research would be more fruitful if individual costs could be recorded by the entrepreneur. Larger repairs should be separated from annual maintenance tasks in a future study. Data from this study could be used to build a life cycle cost model for S&Cs. Practical implications Cost identification is a first step in finding a way to organize maintenance in a more cost-effective way. Originality/valueThe paper shows a way to distribute costs (in the accounting system) down to individual subsystems of the infrastructure. This enables analysts to find cost drivers and plan for modification of or reinvestment in the asset.