The measurement and improvement of track quality are key issues in determining the time at which railway maintenance must be performed and its cost. Efficient track maintenance ensures optimum allocation of limited maintenance resources which has an enormous effect on maintenance efficiency. Applying an appropriate tamping strategy helps reduce maintenance costs, making operations more cost-effective and leading to increased safety and passenger comfort levels. This paper discusses optimisation of the track geometry inspection interval with a view to minimising the total ballast maintenance costs per unit traffic load. The proposed model considers inspection time, the maintenance-planning horizon time after inspection and takes into account the costs associated with inspection, tamping and risk of accidents due to poor track quality. It draws on track geometry data from the iron ore line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to find the probability distribution of geometry faults.

In the past, railway maintenance actions were usually planned based on the knowledge and experience of the infrastructure owner. The main goal was to provide a high level of safety, and there was little concern about economic and operational optimisation issues. Today, however, a deregulated competitive environment and budget limitations are forcing railway infrastructures to move from safety limits to cost-effective maintenance limits to optimise operation and maintenance procedures. By so doing, one widens the discussion to include both operational safety and cost-effectiveness for the whole railway transport system. In this study, a cost model is proposed to specify the cost-effective maintenance limits for track geometry maintenance. The proposed model considers the degradation rates of different track sections and takes into account the costs associated with inspection, tamping, delay time penalties, and risk of accidents due to poor track quality. It draws on track geometry data from the Iron Ore Line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to estimate the geometrical degradation rate of each section. The methodology is based on reliability and cost analysis and facilitates the maintenance decision-making process to identify cost-effective maintenance thresholds.

Turnouts are critical components of track systems in terms of safety, operation and maintenance. Each year, a considerable part of the maintenance budget is spent on their inspection, maintenance and renewal. Applying a cost-effective maintenance strategy helps to achieve the best performance at the lowest possible cost. In Sweden, the geometry of turnouts is inspected at predefined time intervals using the STRIX / IMV 100 track measurement car. This study uses time series for the measured longitudinal level of turnouts on the Iron Ore Line (Malmbanan) in northern Sweden. Two different approaches are applied to analyse the geometrical degradation of turnouts due to dynamic forces generated by train traffic. In the first approach, the recorded measurements are adjusted at the crossing point and then the relative geometrical degradation of turnouts is evaluated by using two defined parameters, the absolute residual area and the maximum settlement, In the second approach, various geometry parameters are defined to estimate the degradation in each measurement separately. The growth rate of the longitudinal level degradation as a function of million gross tonnes / time is evaluated. The proposed methods are based on characterisation of the individual track measurements. 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 can lead to a cost-effective maintenance strategy with optimised inspection and maintenance intervals.

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.

Due to the more or less fixed inherent capacity of a railway system, capacity consuming events like failures within a railway network should be kept to a minimum. This could be achieved by the use of existing and new condition monitoring systems which can detect, report and predict failure events in an early stage. Demands for higher service quality, higher capacity, network availability and track quality together with less human intervention on tracks, drive the development of railway condition monitoring systems.Failure driven capacity consumption due to worn or defected rolling stock wheels have a big impact on the capacity and the infrastructure condition. Wheel defects such as out-of-round wheels, generates high forces, and could result in large capacity consumption especially for areas with cold climate conditions. Bad wheels cause even higher track wear that reduce the life length of the track. Wheels with fatigue defects could also influence the track safety issues. This paper presents how different wheel defects can be monitored; together with a review of the most common wayside condition monitoring systems on the Swedish railway network. The study also describes how the decision making process could take advantage of the condition monitoring data in order to increase the achieved network capacity.

Due to the more or less fixed inherent capacity of a railway system, capacity consuming events like failures within a railway network should be kept to a minimum. This could be achieved by the use of existing and new condition monitoring systems which can detect, report and predict failure events in an early stage. Demands for higher service quality, higher capacity, network availability and track quality together with less human intervention on tracks, drive the development of railway condition monitoring systems.Failure driven capacity consumption due to worn or defected rolling stock wheels have a big impact on the capacity and the infrastructure condition. Wheel defects such as out-of-round wheels, generates high forces, and could result in large capacity consumption especially for areas with cold climate conditions. Bad wheels cause even higher track wear that reduce the life length of the track. Wheels with fatigue defects could also influence the track safety issues. This paper presents how different wheel defects can be monitored; together with a review of the most common wayside condition monitoring systems on the Swedish railway network. The study also describes how the decision making process could take advantage of the condition monitoring data in order to increase the achieved network capacity.

Globally, railway is experiencing a major technology transformation (or paradigm shift), triggered by the enhanced utilisation of digital technology. This technological transformation affects not only the technical systems, i.e. railway infrastructure and rolling stock, but also regulations, organisations, processes,and individuals. Hence, hardware, software, but also liveware (i.e. humans) are affected. Today, the digitalisation of railway is characterised by digital services. There are also a range of challenges, e.g. data acquisition,transformation, modelling, processing, visualisation, safety, security, quality, and information assurance. To deal with these challenges, the railway industry needs to define strategies, which enable a smooth transformation of the existing configuration to a digitalised system. Digital railway requires a holistic change management approach based on system-of-systems thinking and a set of appropriate technologies and methodologies. The railway digitalisation strategy should be based on systematic risk management that address aspects of, e.g., information security, traffic safety and project risk. In addition, managing changes for a digitalised railway effectively and efficiently also requires a framework for aspects such as needs finding, requirement identification, and impact of changes for individual, teams and organisation. In this work a major case studywithin the ePilot, has been performed in context of the operation and maintenance processes of the Swedish railway. Therefore, this paper aims to propose a framework for implementing innovations and driving change in a digitalised railway.

The Swedish ore line, began in 1898 and was completed and operational by 1902. The line was later electrified and remains so to this day. A study on wheel-rail interaction, to optimize wheel and rail profiles on the Malmbanan and Ofoten lines states that there is a need to develop and apply limit values for the allowable length of single and multiple cracks on wheels. Herein, all stakeholders in the railway organization have to be involved. Provisioning of an integrated decision support system for track and vehicle contributes to increased efficiency and improved effectiveness of the maintenance process, which in turn enables achievement of business excellence. However, an integrated decision support process for maintenance is highly dependent on appropriate information logistics which enables information provisioning to various maintenance stakeholders. One emerging approach for development of eMaintenance solutions is utilization of cloud-based technologies. Cloud-based eMaintenance solutions promises smooth information logistics for maintenance decision support. Hence, the purpose of this paper is to propose an approach for condition-based maintenance decision-making relating to railway vehicle wheels, based on a cloud-based eMaintenance solution. The paper also demonstrates how the proposed approach can be implemented for estimation of Remaining Useful Life (RUL) of railway vehicle wheels.

This JVTC report identifies potential maintenance improvements and suggests maintenance actions which will support the reliability of the SSAB railway transport logistic system. Representatives from SSAB, Duroc Rail AB, EuroMaint, AAE, JVTC and SWECO have contributed to this report. 

The SSAB railway transport system needs an extra 23.5% wheel-sets waiting to be used in the maintenance process. Failure mode 331 represents 73 % of all maintained wheel axles. SSAB cost of re-wheeling (IS3) is 12.8 times higher than re-profiling (IS1). LKAB/MTAB cost for IS3 is 4-5 times higher than IS1 cost per wheel-set. An increase in IS1 and a decrease in IS3 lower the total maintenance cost. This result is in line with the full scale test performed by SSAB in 2011.

 More extensive studies on availability, reliability, maintainability, recoverability and maintenance supportability of the transport system should be carried out to find key performance indicators. The goal is to determine mean failure rate, decrease downtime and support maintenance. 

SSAB should establish holistic maintenance processes jointly with the maintenance contractors to ensure consistent application of maintenance and enhanced maintenance support. The work can be organized and managed by a consultancy company with experience in railway operation and maintenance issues.

Contractors must agree on a transparent maintenance information system that includes the following information: wheel-set status descriptions and location data; preventive and corrective maintenance task descriptions; history of preventive and corrective maintenance actions; reports of failures and defects (failure catalogue), including the operating condition when the failure is discovered; condition monitoring data from detectors and manual inspections; economic and maintenance performance data. 

A new work order system should be developed with maintenance tasks based on updated information from the contractors. The work order requests can be triggered automatically by the maintenance information in the system data on predetermined triggers such as wayside detector information, calendar time, elapsed time since last task, and travel distance; alternatively, they can be initiated manually during inspections.

Signalling systems ensure the safe operation of the railway network. Their reliability and maintainability directly affect the capacity and availability of the railway network, in terms of both infrastructure and trains, as a line cannot be fully operative until a failure has been repaired. The purpose of this paper is to propose a data-driven decision support model which integrates the various parameters of corrective maintenance data and to study maintenance performance by considering different RAMS parameters. This model is based on failure analysis of historical events in the form of corrective maintenance actions. It has been validated in a case study of railway signalling systems and the results are summarised. The model allows the creation of maintenance policies based on failure characteristics, as it integrates the information recorded in the various parameters of the corrective maintenance work orders. The model shows how the different failures affect the dependability of the system: the critical failures indicate the reliability of the system, the corrective actions give information about the maintainability of the components, and the relationship between the corrective maintenance times measures the efficiency of the corrective maintenance actions. All this information can be used to plan new strategies of preventive maintenance and failure diagnostics, reduce the corrective maintenance, and improve the maintenance performance.

The railway network is a complex system with several technologies and a multitude of stakeholders working together to solve problems created by the increasing demands on capacity, speed and mobility for the transportation of goods and passengers. However, the presence of many different stakeholders complicates knowledge management and transfer. The purpose of this paper is to analyse the potential for improving inter-organisational knowledge management in the maintenance of railway signalling systems and make concrete suggestions for improvements. Even if information logistics processes can disseminate explicit knowledge on the maintenance of railway signalling systems, they cannot handle the tacit knowledge transfer that often is crucial. The study finds considerable potential for improving the knowledge management process. It suggests possible measures and makes suggestions for future studies.

The service life of a railway wagon wheel can be significantly reduced through failure or damage, leading to excessive costs and accelerated deterioration. In order to monitor the performance of wheels on heavy haul wagons, this paper proposes implementing the Plan, Do, Study, and Act (PDSA) maintenance performance improvement process. As a case study, it looks at wheels on the heavy haul wagons of a Swedish company, considering all factors that may influence the need for maintenance. After investigating the PDSA process, it proposes the use of Key Performance Indicators (KPIs) for both risk and economic reasons. The paper concludes that the PDSA process and KPIs are useful tools to improve the maintenance performance of railway wheels

In Sweden, the railway system is deregulated, with severallayers of operators and contractors. By defining maintenance, its objectives and responsibilities, an operation canbecome cost effective and problem-free. To make this workin a system with many stakeholders, good information flowis crucial. With a holistic computerized information system, each stakeholder can assess maintenance effectiveness, including availability, reliability and maintainability.

For this knowledge to be available, the condition of the railway vehicle assets has to be monitored, either manually and/or withwayside detection equipment. If work orders are automatically generated, human factors (i.e., inconsistency) can bereduced. The article uses a vehicle wheel axle as a casestudy. The maintenance cost for this asset generally represents a large portion of the total maintenance budget; forexample, re-tyring a wheel costs about ten times more thanre-profiling

The railway has been accepted as one of the most environmentally friendly modes of transport for goods and passengers. However, the railway sector is striving to increase its capacity to meet the growing demand for the transport of goods and passengers with a high level of punctuality in its services. Higher availability requires the effective operation and maintenance of infrastructure, often necessitating the implementation of cost-effective preventive maintenance strategies. Therefore, a higher availability target means higher maintenance investment. However, the question of setting the availability target for the infrastructure is not easy, as it involves many influencing decision parameters, apart from a good understanding of the network configuration and traffic density.

Railway networks that have a smaller number of trains and a low punctuality requirement do not require higher availability targets. The aim of this paper is to estimate the availability target for railway infrastructure based on the capacity and punctuality requirements of infrastructure managers and train operating companies.

The objectives of the paper are to develop an approach to i) estimating the capacity of the infrastructure based on the design and operational characteristics and evaluating the influence of infrastructure availability on the required capacity and ii) estimating the volume of primary and secondary delay due to failures and maintenance of the infrastructure and establishing the relationship between availability and punctuality requirements.

To achieve these objectives, an example is presented with parameters drawn from failure, maintenance and traffic data. Finally, a model has been developed in Petri-Nets to establish a relationship between availability, capacity and punctuality. Monte Carlo simulation is used to establish the relationship. The simulation results illustrate the effect of infrastructure availability on train delays and capacity.