A Petri net model for railway bridge maintenance

Le, Bryant; Andrews, John; Fecarotti, Claudia

doi:10.1177/1748006x17701667

Cited by 12 publications

(11 citation statements)

References 31 publications

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“…In particular, the Petri net methodology was considered in order to model asset degradation in the rail sector by Rama et al [51] for rail superstructure, by Andrews et al [52] and Shang et al [53] for track degradation, and by Le et al [54] for rail bridges.…”

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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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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“…Their model includes parts for deterioration, inspection, intervention, and renewal. A similar Petri net model, by the way, is available for bridge maintenance, 21 for instance. Figure 2 shows the degradation part of the model in an extended version with five instead of four health states (i.e.…”

Section: Applicationsmentioning

confidence: 99%

Analyzing uncertainties in model response using the point estimate method: Applications from railway asset management

Neumann

Dutschk

Schenkendorf

2019

Proceedings of the Institution of Mechanical Engineers, Part O:

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Predicting current and future states of rail infrastructure based on existing data and measurements is essential for optimal maintenance and operation of railway systems. Mathematical models are helpful tools for detecting failures and extrapolating current states into the future. This, however, inherently gives rise to uncertainties in the model response that must be analyzed carefully to avoid misleading results and conclusions. Commonly, Monte Carlo simulations are used for such analyses which often require a large number of sample points to be evaluated for convergence. Moreover, even if quite close to the exact distributions, the Monte Carlo approach necessarily provides approximate results only. In contrast to that, the present contribution reviews an alternative way of computing important statistical quantities of the model response. The so-called point estimate method, which can be shown to be exact under certain constraints, usually (i.e. depending on the number of input variables) works with only a few specific sample points. Thus, the point estimate method helps to reduce the computational load for model evaluation considerably in the case of complex models or large-scale applications. To demonstrate the point estimate method, five academic but typical examples of railway asset management are analyzed in more detail: (a) track degradation, (b) reliability analysis of composite systems, (c) terminal reliability in rail networks, (d) failure detection/identification using decision trees, and (e) track condition modeling incorporating maintenance. Advantages as well as limitations of the point estimate method in comparison with common Monte Carlo simulations are discussed.

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“…PNs were developed by the German Carl Adam in the 1962 Adam (1962). Since then, they have been developed and extended to be applied for railway networks Andrews (2013) and bridge risk assessment Le et al (2017). PNs are graphical tools similar to the directed bipartite graphs that can be simulated to analyze existing processes arising in systems with different components.…”

Section: Petri Nets (Pns)mentioning

confidence: 99%

A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

Chahrour¹,

Hariri²,

Tacnet³

et al. 2019

Proceedings of the 29th European Safety and Reliability Conference (ESREL)

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Natural phenomena in mountains put people and assets at risk. Risk reduction measures can be either structural (protection works) or non-structural (risk zoning maps). In torrential watersheds of the French mountains, many checkdams have been built since the 19 th century. As any civil engineered structure, those dams age and their failures may have severe effects on protected areas. Thus, preserving their level of efficacy is of a high interest. In a context of decreasing public budgets, it is necessary to assess their structural, functional and economic efficacy in order to quantify the residual risk and to choose the best maintenance strategies. Recent global approach has been proposed to integrate safety and reliability analysis, multicriteria decision-making methods, and information imperfection processing. However, it does not help in choosing the best strategy to maintain protection devices. It does not cover all aspects related to protection works management making the balance between investment, preventive maintenance costs, and risk evolution. This paper develops a contribution addressing all those issues and proposes a new modeling approach based on Petri nets, whose main steps are: 1) to describe multi-scale protection works systems interaction between both natural and technological systems' components; 2) to analyze structural and functional failure modes; 3) to develop a Petri net model for deterioration and maintenance modeling; 4) to compare different maintenance strategies under different hypothesis on degradation and damage processes.

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A Petri net model for railway bridge maintenance

Cited by 12 publications

References 31 publications

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

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

Analyzing uncertainties in model response using the point estimate method: Applications from railway asset management

A Modeling Framework for Efficacy Assessment and Preventive Maintenance of Torrential Protection Works

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