Per-Olof Larsson-Kråik

Data-driven model for maintenance decision support: A case study of railway signalling systems

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 that integrates the various parameters of corrective maintenance data and to study maintenance performance by considering different reliability, availability, maintainability and safety 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.

Optimisation of track geometry inspection interval

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.

Decision on economical rail grinding interval for controlling rolling contact fatigue

Rail players around the world have been increasing axle loads to improve the productivity of freight and heavy haul operations. This has increased the risk of surface cracks at curves because of rolling contact fatigue. Rail grinding has been considered an effective process for controlling these cracks and reducing risks of rail breaks. The complexity of deciding the optimal rail grinding intervals for improving the reliability and safety of rails is because of insufficient understanding of the various factors involved in the crack initiation and propagation process. This paper focuses on identifying the factors influencing rail degradation, developing models for rail failures and analyzing the costs of various grinding intervals for economic decision making. Various costs involved in rail maintenance, such as rail grinding, downtime, inspection, rail failures and derailment, and replacement of worn-out rails, are incorporated into the total cost model developed in this paper. Field data from the rail industry have been used for illustration.

Evaluation of track geometry maintenance for a heavy haul railroad in Sweden: A case study

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 a 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.

Geometrical degradation of railway turnouts: A case study from a Swedish heavy haul railroad

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.

Cost-effective track geometry maintenance limits

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.

Safety and availability evaluation of railway operation based on the state of signalling systems

A framework is presented to evaluate the safety and availability of the railway operation, and quantifying the probability of the signalling system not to supervise the railway traffic. Since a failure of the signalling systems still allows operation of the railway, it is not sufficient to study their effect on the railway operation by considering only the failures and delays. The safety and availability are evaluated, handling both repairs and replacements by using a Markov model. The model is verified with a case study of Swedish railway signalling systems with different scenarios. The results show that the probability of being in a state where operation is possible in a degraded mode is greater than the probability of not being operative at all, which reduces delays but requires other risk mitigation measures to ensure safe operation. The effects that different improvements can have on the safety and availability of the railway operation are simulated. The results show that combining maintenance improvements to reduce the failure rate and increase the repair rate is more efficient at increasing the probability of being in an operative state and reducing the probability of operating in a degraded state.

Evaluation of technical vs economic decisions in rail grinding

Rail is a significant capital asset for railway companies. It contributes more than half of the capital assets of railway infrastructure. Recent rail inspection data using Ultrasonic rail testing has shown increasing number of rail defects, failures and causing disruptions to rail services. This cost can be further increased when the track quality is poor. In recent years, railroads have been purchasing over 500,000 tons of rails per year at an estimated total cost of US

Development of Wear-Fatigue-Lubrication-Interaction Model for Cost Effective Rail Maintenance Decisions

1.25 billion for replacement of worn out and degraded rails. Rail grinding is considered as viable means in reducing the impacts of rail defects and failures. Rail grinding can result in improved curving performance (wheel/rail interaction) and prevents crack initiation and propagation of surface cracks due to RCF. This paper focuses on analysis of rail degradation process and development of mathematical model considering technical and economic decisions in rail grinding to rail infrastructure owners.

Techniques in Developing Economic Decision Model Combining Above Rail and Below Rail Assets

Prediction of operational risk and enhancement of reliability and safety for rail network are important to rail infrastructure providers and train operators. Rail defects leading to rail breaks and derailments cost huge amount due to cancelled / delayed traffic, emergency maintenance, loss of assets, loss of revenues and liability compensations due to down times. Wear occurring at the wheel/rail interface as a result of ineffective lubrication costs huge amount to rail infrastructure providers per year. Cost of rail-wheel maintenance and replacements are reduced significantly with effective lubrication. Studies on interaction of factors behind wear, fatigue, lubrication and grinding problems are required to monitor those factors and finding out cost effective technological solutions in predicting and reducing operational risks. This paper focuses on development of wear-fatigue-lubrication-interaction model for cost effective rail maintenance decisions.