The capacity demands on the railways will increase in the future, as well as the demands for a robust and available system. The availability of the railway system is dependent on the condition of the infrastructure and the rolling stock. To inspect the rolling stock and to prevent damage to the track due to faulty wheels, infrastructure managers normally install wayside monitoring systems along the track. Such systems indicate, for example, wheels that fall outside the defined safety limits and have to be removed from service to prevent further damage to the track. Due to the nature of many wayside monitoring systems, which only monitor vehicles at definite points along the track, damage may be induced on the track prior to fault detection at the location of the system. Such damage can entail capacity-consuming speed reductions and manual track inspections before the track can be opened for traffic again. The number of wheel defects must therefore be kept to a minimum. In this paper wheel profile parameters measured by a wayside wheel profile measurement system, installed along the Swedish Iron Ore Line, are examined and related to warning and alarm indications from a wheel defect detector installed on the same line. The study shows that an increased wheel wear, detectable by changes in the wheel profile parameters could be used to reduce the risk of capacity-consuming wheel defect failure events and its reactive measures.

Society demand for more sustainable transports is increasing, starting a modal shift from road to railway. The resulting increase in railway traffic intensity is leading to more activities on the track, even during the night time. For many years continuous urbanization has been resulting in a higher density of residents in areas close to railway tracks. The combination of these factors is raising the issue of noise disturbances from railway transports, which is forcing infrastructure managers to take action to combat noise from railway traffic systematically. There are different types of noise emanating from railways and one of the most annoying is curve squeal noise. This paper deals with the curve squeal phenomenon, the places where it occurs, and different methods for reducing it. The curving behaviour of a vehicle plays an important role in the generation of curve squeals, and therefore the way in which different rail profiles affect the capability to steer in a sharp curve is dealt within this paper. The paper is based on two case studies with investigated curves in urban regions that suffer from squeal noise, and in which comparisons between measurements and simulations were performed. The outcome of these studies is a workflow for combating squeal noise, results concerning the effects of a top-of-rail friction modifier on noise mitigation, and a proposed rail profiles for improving the steering capability of vehicles.

The aim of this paper is to present a method for the quality assessment of data from a condition monitoring system for rolling stock wheels to ascertain if the data have the right quality to be used for further analyses. This quality assessment will also show if there are variations between different measurement units for the same system, and if there are relations between different wheel parameter measurements, speed and time. The assessment of data is accomplished using the quality dimension freedom of error. There are two different data sources, namely an automatic wheel profile measurement system and a manual wheel profile measurement device. The manual measurements of wheel profiles are used for verifying the accuracy of the automatic wheel profile measurements, which constitute the larger data set. The proposed method for evaluating the data quality is demonstrated using the data from a specific condition monitoring system. The results show some inconsistencies indicating that this system lacks quality in the dimension of freedom of error and that there is need for internal calibration or self-adjustment of the studied system for quality reasons.

A reliability study based on a Bayesian semi-parametric framework is performed in order to explore the impact of the position of a locomotive wheel on its service lifetime and to predict its other reliability characteristics. A piecewise constant hazard regression model is used to analyse the lifetime of locomotive wheels using degradation data and taking into account the bogie on which the wheel is located. Gamma frailties are included in this study to explore unobserved covariates within the same group. The goal is to flexibly determine reliability for the wheel. A case study is performed using Markov chain Monte Carlo methods and the following conclusions are drawn. First, a polynomial degradation path is a better choice for the studied locomotive wheels; second, under given operational conditions, the position of the locomotive wheel, i.e. on which bogie it is mounted, can influence its reliability; third, a piecewise constant hazard regression model can be used to undertake reliability studies; fourth, considering gamma frailties is useful for exploring the influence of unobserved covariates; and fifth, the wheels have a higher failure risk after running a threshold distance, a finding which could be applied in optimisation of maintenance activities

The Iron Ore Line (IOL) is a 473 km long track section which is located in northern Sweden and northern Norway, and has been in operation since 1903. The northern part is located above the Arctic Circle. The IOL is mainly used to transport iron ore and pellets from the mines in Kiruna and Malmberget to Narvik Harbour (Norway) in the northwest and Luleå Harbour (Sweden) in the southeast. The track section on the Swedish side is owned by the Swedish Government and managed by Trafikverket (the Swedish Transport Administration), while the ore wagons are owned and managed by the freight operator (LKAB).The IOL has seen a considerable increase in the axle load and traffic volume recently. Due to the introduction of new vehicles with a 30-ton axle load, the rails were gradually replaced between 2006 and 2009 with heavier rails, generally with a steel grade of 350LHT. The rail and wheels suffer from rolling contact fatigue (RCF) due to high friction between the rail and wheel. To control the wheel-rail interface, wayside top-of-rail (TOR) lubrication can be used. The reliability of the TOR lubrication equipment and the lubricants in northern conditions has not been investigated, and the long-term maintenance support required for TOR lubrication is unknown to the infrastructure manager. Furthermore, can TOR lubrication reduce the rail and wheel maintenance costs? This project has been conducted through collaboration between the main operator (LKAB) and the infrastructure manager (Trafikverket); the costs have been shared and the results analysed in collaboration. This paper describes the test period of two years, using two different TOR lubrication systems in two different places on the IOL, one situated in the northern loop and one in the southern loop, each with different operational conditions. The paper shows the actual operational conditions for the pilot test locations, the friction value close to the systems, the rail forces during the test period and some results for the noise measurements. Furthermore, the paper includes the improvements of system resulting from the test operation, and ends with recommendations for the continued use of TOR lubrication on the IOL.

The Iron Ore Line (IOL) is a 473 km long track section which is located in northern Sweden and northern Norway, and has been in operation since 1903. The northern part is located above the Arctic Circle. The IOL is mainly used to transport iron ore and pellets from the mines in Kiruna and Malmberget to Narvik Harbour (Norway) in the northwest and Luleå Harbour (Sweden) in the southeast. The track section on the Swedish side is owned by the Swedish Government and managed by Trafikverket (the Swedish Transport Administration), while the ore wagons are owned and managed by the freight operator (LKAB).The IOL has seen a considerable increase in the axle load and traffic volume recently. Due to the introduction of new vehicles with a 30-ton axle load, the rails were gradually replaced between 2006 and 2009 with heavier rails, generally with a steel grade of 350LHT. The rail and wheels suffer from rolling contact fatigue (RCF) due to high friction between the rail and wheel. To control the wheel-rail interface, wayside top-of-rail (TOR) lubrication can be used. The reliability of the TOR lubrication equipment and the lubricants in northern conditions has not been investigated, and the long-term maintenance support required for TOR lubrication is unknown to the infrastructure manager. Furthermore, can TOR lubrication reduce the rail and wheel maintenance costs? This project has been conducted through collaboration between the main operator (LKAB) and the infrastructure manager (Trafikverket); the costs have been shared and the results analysed in collaboration. This paper describes the test period of two years, using two different TOR lubrication systems in two different places on the IOL, one situated in the northern loop and one in the southern loop, each with different operational conditions. The paper shows the actual operational conditions for the pilot test locations, the friction value close to the systems, the rail forces during the test period and some results for the noise measurements. Furthermore, the paper includes the improvements of system resulting from the test operation, and ends with recommendations for the continued use of TOR lubrication on the IOL.

In this paper, the wheel-sets’ running surface wear data based on re-profiling measurement from 16 bogies of heavy haul locomotives at Malmbanan (Sweden) are studied. The case study undertakes: reliability and degradation analysis, wear rate analysis and their comparison (including total wear rate, natural wear rate, re-profiling wear rate, the ratio of re-profiling and natural wear). The results show that: 1) for the studied group, a linear degradation path is more suitable; 2) following the linear degradation, the best life distribution is a 3-parameter Weibull distribution; 3) comparing the wearing data of the wheel-sets’ running surfaces is an effective way to optimize maintenance strategies; 4) more natural wear occurs for the wheels installed in axle 1 and axle 3, supportive evidence for other related studies at Malmbanan.

Friction management in the railway industry is a well-established technology with the aim of optimizing the friction between the wheel and rail. Determining the friction coefficient (μ) at the wheel-rail interface is therefore important especially for heavy haul lines with higher axle loads. This paper presents an initial study of the top-of-rail friction condition of a line with 30 ton axle load, the Iron Ore Line in the northern part of Sweden. The friction coefficient between the rail and the metal wheel of a portable tribometer was measured at different geographical locations and in different environmental conditions. The effects of precipitation are studied and compared with the effects of top-of-rail friction modifiers.The measurements of non-lubricated line sections showed values of μ≈0.6, compared to μ≈0.3 for areas with, for example, top-of- rail lubrication. In snowy conditions a decrease in friction could also be detected.Keywords: Friction management, Friction measurement, Friction modifier, Heavy haul railway line, Swedish Iron Ore Line.

Railway transport system is massive and complex, and as such it requires effective maintenance to achieve the business goal of safe, economic and sustainable transportation of passengers and goods. The growing demand for improved service quality and capacity target by railway infrastructure managers requires appropriate maintenance analysis to facilitate continuous improvement of infrastructure performance. This paper presents the application of risk matrix as a maintenance analysis method for the identification of track zones that are bottlenecks that limit operational capacity and quality. Furthermore, an adapted analysis method is proposed to create a hierarchical improvement list for addressing the problem of train mission interruption and reduced operational capacity. A case study of a line section of the Swedish network is presented. The result classifies the zones on the line section into different risk categories based on their contribution to loss of capacity and punctuality. In addition, an improvement list for the lower-level system is presented to facilitate maintenance decisions and continuous improvement at both operational and strategic levels.

This paper undertakes a general reliability study using both classical and Bayesian semi-parametric degradation approaches. The goal is to illustrate how degradation data can be modelled and analysed to flexibly determine reliability to support preventive maintenance strategy making, based on a general data-driven framework. With the proposed classical approach, both Accelerated Life Tests (ALT) and Design of Experiments (DOE) technology are used to determine how each critical factor affects the prediction of performance. With the Bayesian semi-parametric approach, a piecewise constant hazard regression model is used to establish the lifetime using degradation data. Gamma frailties are included to explore the influence of unobserved covariates within the same group. Ideally, results from the classical and Bayesian approaches will complement each other. To demonstrate these approaches, this paper considers a case study of locomotive wheel-set reliability. The degradation data are prepared by considering an Exponential and a Power degradation path separately. The results show that both classical and Bayesian semi-parametric approaches are useful tools to analyse degradation data and can, therefore, support a company in decision making for preventive maintenance. The approach can be applied to other technical problems (e.g. other industries, other components).