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

2014 ◽  
Vol 230 (1) ◽  
pp. 220-234 ◽  
Author(s):  
Amparo Morant ◽  
Per-Olof Larsson-Kråik ◽  
Uday Kumar
Keyword(s):  
Decision Support ◽  
Data Driven ◽  
Maintenance Decision ◽  
Railway Signalling ◽  
Signalling Systems

A Data-Driven Decision Support Tool at the service of Energy suppliers and Utilities for Tackling Energy Poverty: A case study in Greece

2021 ◽  
Author(s):  
Apostolos Arsenopoulos ◽  
Elissaios Sarmas ◽  
Andriana Stavrakaki ◽  
Ioanna Giannouli ◽  
John Psarras
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Data Driven ◽  
Energy Poverty ◽  
Support Tool

scholarly journals Benefits of lubricant oil analysis for maintenance decision support: a case study

2018 ◽  
Vol 393 ◽  
pp. 012013
Author(s):  
V V Karanović ◽  
M T Jocanović ◽  
J M Wakiru ◽  
M D Orošnjak
Keyword(s):  
Decision Support ◽  
Oil Analysis ◽  
Lubricant Oil ◽  
Maintenance Decision

Maintenance analytics for railway infrastructure decision support

2017 ◽  
Vol 23 (3) ◽  
pp. 310-325 ◽  
Author(s):  
Stephen Mayowa Famurewa ◽  
Liangwei Zhang ◽  
Matthias Asplund
Keyword(s):  
Decision Support ◽  
Anomaly Detection ◽  
Practical Implication ◽  
Measurement Data ◽  
Content Type ◽  
Rail Wear ◽  
Railway Infrastructure ◽  
Maintenance Decision ◽  
Infrastructure Maintenance

Purpose The purpose of this paper is to present a framework for maintenance analytics that is useful for the assessment of rail condition and for maintenance decision support. The framework covers three essential maintenance aspects: diagnostic, prediction and prescription. The paper also presents principal component analysis (PCA) and local outlier factor methods for detecting anomalous rail wear occurrences using field measurement data. Design/methodology/approach The approach used in this paper includes a review of the concept of analytics and appropriate adaptation to railway infrastructure maintenance. The diagnostics aspect of the proposed framework is demonstrated with a case study using historical rail profile data collected between 2007 and 2016 for nine sharp curves on the heavy haul line in Sweden. Findings The framework presented for maintenance analytics is suitable for extracting useful information from condition data as required for effective rail maintenance decision support. The findings of the case study include: combination of the two statistics from PCA model (T2 and Q) can help to identify systematic and random variations in rail wear pattern that are beyond normal: the visualisation approach is a better tool for anomaly detection as it categorises wear observations into normal, suspicious and anomalous observations. Practical implications A practical implication of this paper is that the framework and the diagnostic tool can be considered as an integral part of e-maintenance solution. It can be easily adapted as online or on-board maintenance analytic tool with data from automated vehicle-based measurement system. Originality/value This research adapts the concept of analytics to railway infrastructure maintenance for enhanced decision making. It proposes a graphical method for combining and visualising different outlier statistics as a reliable anomaly detection tool.

scholarly journals Reliability and Inspection Modelling of Railway Signalling Systems

Modelling ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 344-354
Author(s):  
Nikesh Kumar ◽  
Kong Fah Tee
Keyword(s):  
High Reliability ◽  
Signalling System ◽  
System A ◽  
Long Run ◽  
Modelling Techniques ◽  
Inspection And Maintenance ◽  
Railway Signalling ◽  
Railway Operation ◽  
Signalling Systems

The railway is one of the most prominent models of transportation across the globe and it carries a large number of people, thus requiring high reliability, maintainability and safety. The reliability of railways mostly depends on an effective signalling system, making it one of the critical parts of railway operation. A signalling system is part of a large array of systems with interconnected components and subcomponents. Therefore, there is a need to make the signalling system more reliable and optimised with enhanced fault detection. Proper inspection and maintenance are required to make the signalling system reliable and safe. In this study, different inspection modelling techniques are applied to find the reliability of the signalling system. The signalling system has been divided into subsystems (signal unit, track unit, point-and-point machine) considering their importance and their effects on the failure rate of the entire signalling system. Inspection modelling of each subsystem has been conducted to provide the basis for the entire signalling system. A case study has been investigated to validate the model developed in one of the busiest tracks in eastern India. The obtained data thus are used to analyse the inspection pattern of signalling subsystems. Special attention to maintenance for inspection activities and logistics support has been taken into consideration, which is required to improve the reliability and maintainability of signalling subsystems and systems to make the railway signalling system sustainable in the long run.

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

2016 ◽  
Vol 231 (2) ◽  
pp. 226-238 ◽  
Author(s):  
Amparo Morant ◽  
Anna Gustafson ◽  
Peter Söderholm ◽  
Per-Olof Larsson-Kråik ◽  
Uday Kumar
Keyword(s):  
Markov Model ◽  
Risk Mitigation ◽  
Mitigation Measures ◽  
Safe Operation ◽  
Repair Rate ◽  
Railway Traffic ◽  
Railway Signalling ◽  
Railway Operation ◽  
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.

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