Railway Infrastructure Assets Research Articles

A Proactive Decision-Making Model for Evaluating the Reliability of Infrastructure Assets of a Railway System

Railway infrastructure is generally classified as either fixed or movable infrastructure assets. Failure in any of the assets could lead to the complete shutdown and disruption of the entire system, economic loss, inconvenience to passengers and the train operating company(s), and can sometimes result in death or injury in the event of the derailment of the rolling stock. Considering the importance of the railway infrastructure assets, it is only necessary to continuously explore their behavior, reliability, and safety. In this paper, a proactive multi-criteria decision-making model that is based on an interval-valued intuitionistic fuzzy set and some reliability quantitative parameters has been proposed for the evaluation of the reliability of the infrastructure assets. Results from the evaluation show that the failure mode ‘Broken and defective rails’ has the most risk and reliability concerns. Hence, priority should be given to the failure mode to avoid a total system collapse.

Climate change impacts assessment on railway infrastructure in urban environments

Climate change impacts can escalate the deteriorating rate of infrastructures and impact the infrastructure's functionality, safety, operation and maintenance (O&M). This research explores climate change's influence on urban railway infrastructure. Given the geographical diversity of Sweden, the railway network is divided into different climate zones utilizing the K-means algorithm. Reliability analysis using the Cox Proportional Hazard Model is proposed to integrate meteorological parameters and operational factors to predict the degree of impacts of different climatic parameters on railway infrastructure assets. The proposed methodology is validated by selecting a number of switches and crossings (S&Cs), which are critical components in railways for changing the route, located in different urban railway stations across various climate zones in Sweden. The study explores various databases and proposes a climatic feature to identify climate-related risks of S&C assets. Furthermore, different meteorological covariates are analyzed to understand better the dependency between asset health and meteorological parameters. Infrastructure asset managers can tailor suitable climate adaptation measures based on geographical location, asset age, and other life cycle parameters by identifying vulnerable assets and determining significant covariates. Sensitivity analysis of significant covariates at one of the urban railway stations shows precipitation increment reveal considerable variation in the asset reliability.

Optimization of Railway Infrastructure Asset – A Review

Railway infrastructure assets are key components in the railway transportation system. Optimal asset management is essential to improve the efficiency and productivity of the railway system, as well as help prevent unnecessary costs in the asset life cycle. Reliability, Availability, Maintainability, and Safety (RAMS) and Life Cycle Cost (LCC) methods can be used in managing railway infrastructure assets. RAMS is a method used to assess the performance of high-complexity systems such as rail infrastructure systems. In contrast, LCC is used to evaluate the overall cost of a system or asset over the life cycle. Integrating RAMS and LCC concepts can help plan railways' design, operation, and maintenance. This integration is very flexible as it can be done from the life cycle's design, operation, and maintenance stages. Research shows that using the integration of RAMS and LCC can lead to better strategic decisions in the life cycle of a railway. In selecting assets to support design and maintenance, for example, there are two high-speed rail double-track alternatives of ballasted and ballastless track, with results showing that ballastless track has higher RAMS performance and lower maintenance cost but higher construction costs, so ballasted track solutions are preferred for short-term construction and the ballastless track is preferred for long-term.

A global multi-hazard risk analysis of road and railway infrastructure assets

Transport infrastructure is exposed to natural hazards all around the world. Here we present the first global estimates of multi-hazard exposure and risk to road and rail infrastructure. Results reveal that ~27% of all global road and railway assets are exposed to at least one hazard and ~7.5% of all assets are exposed to a 1/100 year flood event. Global Expected Annual Damages (EAD) due to direct damage to road and railway assets range from 3.1 to 22 billion US dollars, of which ~73% is caused by surface and river flooding. Global EAD are small relative to global GDP (~0.02%). However, in some countries EAD reach 0.5 to 1% of GDP annually, which is the same order of magnitude as national transport infrastructure budgets. A cost-benefit analysis suggests that increasing flood protection would have positive returns on ~60% of roads exposed to a 1/100 year flood event.

A risk-based modelling approach to maintenance optimization of railway rolling stock

Purpose Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components. Design/methodology/approach All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components. Findings For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies. Practical implications The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed. Originality/value There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.

Multi-objective model for optimizing railway infrastructure asset renewal

ABSTRACTA multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.

Risk Evaluation of Railway Rolling Stock Failures Using FMECA Technique: A Case Study of Passenger Door System

Railway transport consists of two main asset classes of infrastructure and rolling stock. To date, there has been a great deal of interest in the study and analysis of failure mechanisms for railway infrastructure assets, e.g. tracks, sleepers, bridges, signalling system, electrical units, etc. However, few attempts have been made by researchers to develop failure criticality assessment models for rolling stock components. A rolling stock failure may cause delays and disruptions to transport services or even result in catastrophic derailment accidents. In this paper, the potential risks of unexpected failures occurring in rolling stock are identified, analysed and evaluated using a failure mode, effects and criticality analysis-based approach. The most critical failure modes in the system with respect to both reliability and economic criteria are reviewed, the levels of failure criticality are determined and possible methods for mitigation are provided. For the purpose of illustrating the risk evaluation methodology, a case study of the Class 380 train’s door system operating on Scotland’s railway network is provided and the results are discussed. The data required for the study are partly collected from the literature and unpublished sources and partly gathered from the maintenance management information system available in the company. The results of this study can be used not only for assessing the performance of current maintenance practices, but also to plan a cost-effective preventive maintenance (PM) programme for different components of rolling stock.

Railway infrastructure asset management: the whole‐system life cost analysis

Delivering the railway infrastructure whose functionality is sustainable and uncompromised in terms of safety and availability under ever decreasing budget constraints is a great challenge. The successful accomplishment of this task relies on the effective management of individual assets within a wider whole system perspective. This is a highly complex decision-making task where mathematical models are required to enable well-informed choices. In this study, a novel modelling framework is proposed for performing the whole system lifecycle cost analysis. The framework is based on two models: railway network performance and costs. Using the former model investigations of the effects of decisions can be carried out for the individual asset and the whole system. A Petri net modelling technique is used to construct the model. A form of Monte Carlo simulation is then used to obtain model results. The infrastructure performance model is then integrated with the cost model to perform the lifecycle cost analysis. A superstructure example is presented to demonstrate the application of the approach. The results show that taking into account interdependencies among the intervention activities greatly influences, not only the performance of the infrastructure, but also its lifecycle costs and thus should be included in the cost analysis.

Data Analysis for Condition‐Based Railway Infrastructure Maintenance

Condition assessment is crucial to optimize condition-based maintenance actions of assets such as railway infrastructure, where a faulty state might have severe consequences. Hence, railways are regularly inspected to detect failure events and prevent the inspected item (e.g. rail) to reach a faulty state with potentially safety critical consequences (e.g. derailment). However, the preventive measures (e.g. condition-based maintenance) initiated by the inspection results may cause traffic disturbances, especially if the expected time to a faulty state is short. The alarm limits are traditionally safety related and often based on geometrical properties of the inspected item. Maintenance limits would reduce the level of emergency, producing earlier alarms and increasing possibilities of planned preventive rather than acute maintenance. However, selecting these earlier maintenance limits in a systematic way while balancing the risk of undetected safety-critical faults and false alarms is challenging. Here, we propose a statistically based approach using condition data of linear railway infrastructure assets. The data were obtained from regular inspections done by a railway track measurement wagon. The condition data were analysed by a control chart approach to evaluate the possibility for earlier detection of derailment hazardous faults using both temporal and spatial information. The study indicates that that the proposed approach could be used for condition assessment of tracks. Control charts led to earlier fault warnings compared to the traditional approach, facilitating planned condition-based maintenance actions and thereby a reduction of track downtime. Copyright © 2014 The Authors. Quality and Reliability Engineering International published by John Wiley & Sons, Ltd.

Special issue on Railway Infrastructure Asset Management

Special issue on Railway Infrastructure Asset Management