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

Rama, Dovile; Andrews, John

doi:10.1049/iet-its.2015.0030

Cited by 22 publications

(12 citation statements)

References 9 publications

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“…Risk assessment techniques such as Monte Carlo simulations, Bayesian, Fuzzy logic and Petri nets are recommended to deal with such uncertainties (Rama & Andrews, 2016;Sasidharan & Torbaghan, 2020;Zhang & Wang, 2014). Majority of these techniques use historical data and probability judgements, and conclusions on the acceptability of the solutions are often made directly based on derived probabilities and confidence levels.…”

Section: Uncertaintiesmentioning

confidence: 99%

Risk-informed asset management to tackle scouring on bridges across transport networks

Sasidharan

Parlikad

Schooling

2021

Structure and Infrastructure Engineering

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Scour is one of the main causes of bridge failures resulting in significant macroeconomic impacts, often beyond the direct costs of infrastructure damage. Given the pressure to increase the resilience of transport networks, ageing bridge infrastructure, constrained budgets, variable knowledge of asset conditions and limited data, mixed ownership and operation of bridges, and concerns about the risks of climate change, there is a need to implement cost-effective monitoring and maintenance strategies. To this end, this study aims to set the scene for a risk-informed approach for tackling bridge scour, while considering the socioeconomic impacts of disruptions due to bridge failures or closures. This study reviews the current practices in predicting, monitoring and managing bridge scour. It discusses the development of a risk-informed approach to aid the whole-life appraisal of bridges while considering the direct and indirect costs associated with bridge failure or closures. The approach provides a rational means to enable asset managers to evaluate the factors that affect bridge failure risk, select and prioritise appropriate mitigation measures, thereby improving the allocation of scarce monitoring and maintenance resources.

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Section: Uncertaintiesmentioning

confidence: 99%

Risk-informed asset management to tackle scouring on bridges across transport networks

Sasidharan

Parlikad

Schooling

2021

Structure and Infrastructure Engineering

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“…In the rail sector, works deal with the introduction of sustainability concepts in asset management, applying a whole-system life cost analysis [12][13][14].…”

Section: Literature Reviewmentioning

confidence: 99%

On Applying Machine Learning and Simulative Approaches to Railway Asset Management: The Earthworks and Track Circuits Case Studies

et al. 2020

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The objective of this study is to show the applicability of machine learning and simulative approaches to the development of decision support systems for railway asset management. These techniques are applied within the generic framework developed and tested within the In2Smart project. The framework is composed by different building blocks, in order to show the complete process from data collection and knowledge extraction to the real-world decisions. The application of the framework to two different real-world case studies is described: the first case study deals with strategic earthworks asset management, while the second case study considers the tactical and operational planning of track circuits’ maintenance. Although different methodologies are applied and different planning levels are considered, both the case studies follow the same general framework, demonstrating the generality of the approach. The potentiality of combining machine learning techniques with simulative approaches to replicate real processes is shown, evaluating the key performance indicators employed within the considered asset management process. Finally, the results of the validation are reported as well as the developed human–machine interfaces for output visualization.

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“…A framework for modelling railway infrastructure reliability, based on the hierarchical representation of the railway network, was presented by Rama and Andrews [8], [35]. The model allows performance analysis to be conducted at varying levels of detail, ranging from an individual maintainable item to large multi-asset networks.…”

Section: Modelling Railway Infrastructure Reliabilitymentioning

confidence: 99%

“…This presents challenges in defining the correct functional and operational configuration required to model the lifecycle performance of infrastructure systems. The benefits of prioritising, categorising, and improving intervention activities among the different infrastructure asset groups vary from improved infrastructure reliability performance to a reduction in operational and maintenance expenditures [8]. To improve the reliability performance of railway infrastructure systems effectively requires a whole-systems approach to railway infrastructure reliability modelling.…”

Section: Introductionmentioning

confidence: 99%

A Modelling Framework for Railway Infrastructure Reliability Analysis

Fourie

Zhuwaki

2017

SAJIE

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The maintenance and management of railway infrastructure plays a central role in ensuring the reliability and availability of rail transport. In a highly competitive transport market, the rail industry is required to employ new and innovative maintenance strategies that will position rail transport as an affordable and reliable transportation alternative. This can be realised through implementing maintenance strategies that prioritise efficient resource allocation. Application of reliability-based techniques to make informed decisions in maintenance management, with an overall aim of reducing operational expenditure while maintaining safety and efficiency, has been increasing. This paper presents a framework for the application of a reliability-based technique to evaluate the reliability of railway infrastructure systems. OPSOMMINGDie onderhoud en bestuur van spoorweginfrastruktuur speel 'n sentrale rol om die betroubaarheid en beskikbaarheid van spoorverkeer te verseker. In 'n hoogs-mededingende vervoer bedryf, word dit van die spoorindustrie verwag om nuwe en innoverende onderhoudstrategieë toe te pas. Dit sal dié industrie in die posisie stel om 'n bekostigbare en betroubare vervoerkeuse te wees. Hierdie posisie kan egter slegs bereik word indien onderhoudstrategieë toegepas word wat voorkeur gee aan die doeltreffende toewysing van hulpbronne. Daar is 'n toename in die toepassing van tegnieke gegrond op betroubaarheid vir die neem van ingeligte besluite in onderhoudbestuur. Die doel van die tegnieke is om bedryfsuitgawes te verminder terwyl veiligheid en doeltreffendheid behoue bly. In hierdie artikel word 'n raamwerk voorgestel vir die toepassing van tegnieke om betroubaarheid van spoorweginfrastruktuur te evalueer. INTRODUCTIONThe management of railway infrastructure assets involves a range of activities such as building, inspection, maintenance, enhancement, and renewal aimed at optimising the performance, risks, and costs of the infrastructure. This is a highly complex decision-making environment that requires various trade-offs. Furthermore, the relationship between the timing and choice of activities for multiple assets needs to be taken into account to achieve the required performance levels. Significant efforts have been made to develop decision support tools based on cost, risk, and reliability to assist with decision-making in highly complex asset management environments. used reliability-based techniques to develop a parametric model to predict correctly the failure rate probability of point-and-point machines in railway signalling subsystems. Additionally, similar reliability analyses using fault tree analysis have been applied to railway infrastructure systems to quantify the reliability performance of railway electrical subsystems [5]- [7].

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

Cited by 22 publications

References 9 publications

Risk-informed asset management to tackle scouring on bridges across transport networks

Risk-informed asset management to tackle scouring on bridges across transport networks

On Applying Machine Learning and Simulative Approaches to Railway Asset Management: The Earthworks and Track Circuits Case Studies

A Modelling Framework for Railway Infrastructure Reliability Analysis

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