Special Issue "Modelling for Reliability and Maintenance Engineering"

A special issue of Modelling (ISSN 2673-3951).

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Assoc. Prof. Phuc Do
E-Mail Website
Guest Editor
University of Lorraine, Campus sciences BP70239, 54506 Vandoeuvre Cedex, France
Interests: degradation and reliability modelling; prognostics of key performance indicators; maintenance modelling and optimization
Assoc. Prof. Cristiano Cavalcante
E-Mail Website
Guest Editor
Universidade Federal de Pernambuco (Federal University of Pernambuco), Av. da Arquitetura, s/n. Prédio do Departamento de Engenharia de Produção, Sala 201 A. CEP: 50740-550, Cidade Universitária, Recife-PE, Brasil
Interests: operational research; maintenance modelling and optimization; risk; reliability; safety; warehouse management and logistics

Special Issue Information

Dear Colleagues,

The growing human dependence on technological systems, as well as the ground-breaking changes in production processes, has recently placed maintenance and reliability factors at a hitherto unforeseen level of importance. New techniques have been emerging from different areas and are being associated with classical approaches in maintenance and reliability to help to handle massive amounts of data, the need to do this being one of the main features of the current manufacture revolution. Thus, a broader effort in research is imperative so that the role of reliability and maintenance in these new challenges can be adequately defined and able to meet the constant demands for this. For the reasons mentioned above, this Special Issue of Modelling seeks to attract relevant contributions on reliability and maintenance modeling. Therefore, the Guest Editors invite submissions with an original perspective and advanced thinking on this topic and related issues. We welcome original research papers with theoretical development and solid empirical grounding on any one or more of (but not limited to) the following topics:

  • degradation modeling and reliability assessment;
  • reliability analysis;
  • prognostics and health management;
  • reliability and maintenance engineering;
  • digital twin for reliability and maintenance;
  • reinforcement learning for maintenance decision-making;
  • machine learning for reliability;
  • reliability and maintenance modeling for cyber–physical systems;
  • maintenance for industry 4.0;
  • life cycle/performance analysis;
  • spare parts supply chain management;
  • warranty management and data analysis.


Assoc. Prof. Phuc Do
Assoc. Prof. Cristiano Cavalcante
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Modelling is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • degradation modeling
  • reliability
  • maintenance
  • prognostics
  • digital twin
  • machine learning
  • cyber–physical systems

Published Papers (1 paper)

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Case Report
Reliability and Inspection Modelling of Railway Signalling Systems
Modelling 2021, 2(3), 344-354; https://doi.org/10.3390/modelling2030018 - 26 Jul 2021
Viewed by 197
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Modelling for Reliability and Maintenance Engineering)
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