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The purpose of this paper is to demonstrate how research within the railway sector is developing eMaintenance solutions using the cloud and web-based applications for improved condition monitoring, better maintenance and increased uptime. This eMaintenance solution is based on the on-line data acquisition, integration and analysis leading to effective maintenance decision making.

In the proposed methodology, data are acquired from railway measurement stations to the eMaintenance cloud, where they are filtered, fused, integrated and analysed to assist maintenance decisions. Extensive consultation with stakeholders has resulted in the analysis of railway data.

The paper provides a concept for a web-based eMaintenance solution for railway maintenance stakeholders for making fact-based decisions and develops more efficient and economically sound maintenance policies. Train wheels reaching their maintenance and safety limits are visualised in grids and graphs to assist stakeholders in making the appropriate maintenance decisions.

In this paper the authors have demonstrated that the wheel profile and force data can be remotely collected through cloud utilisation. The information generated can be used for maintenance decision making. Similarly, other measurable data can also be utilised for maintenance decision making.

This paper describes the importance of eMaintenance solution through online data analysis to make effective and efficient railway maintenance decisions, as a case study.

The purpose of this paper is to explore the main ontologies related to eMaintenance solutions and to study their application area. The advantages of using these ontologies to improve and control data quality will be investigated.

A literature study has been done to explore the eMaintenance ontologies in the different areas. These ontologies are mainly related to content structure and communication interface. Then, ontologies will be linked to each step of the data production process in maintenance.

The findings suggest that eMaintenance ontologies can help to produce a high-quality data in maintenance. The suggested maintenance data production process may help to control data quality. Using these ontologies in every step of the process may help to provide management tools to provide high-quality data.

Based on this study, it can be concluded that further research could broaden the investigation to identify more eMaintenance ontologies. Moreover, studying these ontologies in more technical details may help to increase the understandability and the use of these standards.

It has been concluded in this study that applying eMaintenance ontologies by companies needs additional cost and time. Also the lack or the ineffective use of eMaintenance tools in many enterprises is one of the limitations for using these ontologies.

Investigating eMaintenance ontologies and connecting them to maintenance data production is important to control and manage the data quality in maintenance.

The purpose of this paper is mainly to highlight how a simplified and streamlined approach to the condition monitoring (CM) of industrial rotating machines through the application of frequency domain data combination can effectively enhance the eMaintenance framework.

The paper commences by providing an overview to the relevance of maintenance excellence within manufacturing industries, with particular emphasis on the roles that rotating machines CM of rotating machines plays. It then proceeds to provide details of the eMaintenance as well as its possible alignment with the introduced concept of effective vibration-based condition monitoring (eVCM) of rotating machines. The subsequent sections of the paper respectively deal with explanations of data combination approaches, experimental setups used to generate vibration data and the theory of eVCM.

This paper investigates how a simplified vibration-based rotating machinery faults classification method based on frequency domain data combination can increase the feasibility and practicality of eMaintenance.

The eVCM approach is based on classifying data acquired under several experimentally simulated conditions on two different machines using combined higher order signal processing parameters so as to reduce CM data requirements. Although the current study was solely based on the application of vibration data acquired from rotating machines, the knowledge exchange platform that currently dominates present day scientific research makes it very likely that the lessons learned from the development of eVCM concept can be easily transferred to other scientific domains that involve continuous CM such as medicine.

The concept of eMaintenance as a cost-effective and smart means of increasing the autonomy of maintenance activities within industries is rapidly growing in maintenance-related literatures. As viable as the concept appears, the achievement of its optimum objectives and full deployment to the industry is still subjective due to the complexity and data intensiveness of conventional CM practices. In this paper, an eVCM approach is proposed so that rotating machine faults can be effectively detected and classified without the need for repetitive analysis of measured data.

The main strength of eVCM lies in the fact that it permits the sharing of historical vibration data between identical rotating machines irrespective of their foundation structures and speed differences. Since eMaintenance is concerned with driving maintenance excellence, eVCM can potentially contribute towards its optimisation as it cost-effectively streamlines faults diagnosis. This therefore implies that the simplification of vibration-based CM of rotating machines positively impacts the society with regard to the possibility of reducing how much time is actually spent on the accurate detection and classification of faults.

Although the currently existing body of literature already contains studies that have attempted to show how the combination of measured vibration data from several industrial machines can be used to establish a universal vibration-based faults diagnosis benchmark for incorporation into eMaintenance framework, these studies are limited in the scope of faults, severity and rotational speeds considered. In the current study, the concept of multi-faults, multi-sensor, multi-speed and multi-rotating machine data combination approach using frequency domain data fusion and principal components analysis is presented so that faults diagnosis features for identical rotating machines with different foundations can be shared between industrial plants. Hence, the value of the current study particularly lies in the fact that it significantly highlights a new dimension through which the practical implementation and operation of eMaintenance can be realized using big data management and data combination approaches.

The purpose of this paper is to explore the transferability of ICT‐solutions for providing support information services from eHealth to eMaintenance.

The applied research approach takes the form of a single‐case study supported by a literature study. Empirical data were collected through documents, observations and interviews. The conclusions of the study were verified by key informants.

The study indicates some major problems that have to be overcome when implementing support information services using an ICT‐solution (e.g. to manage heterogeneous organizations; manage heterogeneous eService‐environments; and enable context and situation awareness in eServices). Further, the study has identified and graded some solutions, which address these problems and are transferable from eHealth to eMaintenance.

The studied case is in the forefront of eHealth solutions and can therefore act as a guidance for those involved at different stages of eHealth implementation. At the same time, eHealth is an application domain with stringent safety and security requirements, which makes the findings valuable for persons involved in support information services related to complex and critical technical systems, e.g. aircraft systems.

The paper reports on experiences from an actual eHealth solution and not just about the concept of eHealth. Hence, it has implications for both practitioners and researchers.

The purpose of this paper is to describe a taxonomy for an eMaintenance management framework (eMMF) based on a service‐oriented approach, in order to facilitate the development of information and communication technology (ICT)‐based maintenance support services aimed at actors within the maintenance process related to complex technical industrial systems.

To fulfil this purpose, a case study of a modern multi‐role combat aircraft is selected as an appropriate research strategy and supported by a literature study. Empirical data are collected through interviews, workshops, document studies, and observations. A framework is developed and evaluated using a prototype within the studied case. The study is performed in close cooperation with the aircraft's type certificate holder and the customer representative and operator in one country.

The proposed eMMF aids in the identification and development of ICT‐based maintenance support services tailored for specific maintenance actors and their activities.

To further test the usefulness of the proposed framework, a larger scale application must be performed. This can involve additional stakeholders or a larger part of the technical system in the selected case, or another case dealing with complex technical industrial systems.

The proposed framework supports the identification of required information services that support the maintenance process, which in turn supports the development of a service‐oriented architecture (SOA) aimed at proper maintenance information logistics. Hence, people working with information logistics for maintenance purposes can use the framework as a support tool.

The proposed framework combines a process and service‐oriented approach, which facilitates the development of SOA‐based information services by giving valuable input to more traditional system‐oriented approaches.

The purpose of this paper is to explore and study the aspects of usability related to eMaintenance solutions. The study aims to expand the domain of eMaintenance by increasing the usefulness of the computerized maintenance management systems (CMMS) through improved usability.

The paper opted for an exploratory study using interviews, one expert focus group discussion, and observations.

The paper provides insights on specific usability characteristics that can be adapted to eMaintenance solutions for industrial usage, e.g. aviation and process industry. The findings show that the current implementations of eMaintenance solutions in CMMS, in many cases, suffer from an insufficient level of usability. This has led to usability issues resulting in errors and mistakes. The result is a call for a more user-based focus, in which, the system needs to be easily understood, easily navigated, containing the necessary information to conduct maintenance tasks, tracking of the work conducted and who was involved, and the system needs to be compatible with other systems so that necessary information can be accessed via the CMMS.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

The paper includes implications for the development of a CMMS, which could have positive effects for maintenance tasks.

This paper fulfills an identified need to study how CMMS actually fulfill the task they are designed to do.

The purpose of this research paper is to evaluate and estimate the cybersecurity maturity and awareness risk for workforce management in railway transportation by using Railway-Cybersecurity Capability Maturity Model (R-C2M2) and Information Security Awareness Capability Model (ISACM), respectively.

This research uses a case study strategy, so primary data comprise the majority of data collected. These data were collected through interviews and questionnaires. The secondary data were collected from the literature, technical reports and standards.

The results show that there is a gap in cybersecurity awareness within the workforce and there is a need to improve this gap. This paper provides some of the recommendations and literature to enhance cybersecurity workforce culture within railway organizations.

In this paper, the authors have demonstrated that cybersecurity awareness has positive impact on the overall dependability of the railway system.

This paper describes the importance of cybersecurity awareness and training in building more cyber resiliency across the operation and maintenance of railway.

The purpose of this paper is to provide a literature review of the performance measurement (PM) in maintenance. The authors aim to discuss the background and development of the PM for maintenance, besides defining the concept of performance measures for maintenance and the frameworks developed.

A detailed and extensive literature search and study was undertaken by the authors on the concept and definition of PM, performance indicators (PIs), maintenance performance indicators and various performance frameworks. The history and theory of PM over different phases of business and technological developments have been critically examined and analysed in this review paper.

This paper reviews and presents the different PIs and PM frameworks like; balanced scorecard (BSC), performance prism, performance pyramid and performance matrix, etc., and identifies their characteristics and shortcomings. After considering related issues and challenges, frameworks and approaches for the maintenance performance measurement (MPM) are also presented, where the emerging techniques like; emaintenance have also been discussed amongst others. More and more industries are applying the balanced and integrated MPM frameworks for their competitive survivability and sustainability.

The concept, issues and approaches considered for the MPM frameworks can be adapted by the practicing managers, while trying to define and develop an MPM framework for the operation and maintenance activities. The considerations of the advantages and limitations of different frameworks can provide insights to the managers for implementation.

Some literature reviews on MPM and MPM frameworks are available today. This paper makes an attempt to provide a detailed and relevant literature review, besides adding value in this new and emerging area.

Uncovering the relationship between Industry 4.0 (I4.0) technologies and circular economy (CE) practices is critical not only for implementing CE but also for leveraging I4.0 to achieve sustainable development goals. However, the potential connection between them – especially how different I4.0 technologies may influence various CE practices – remains inadequately researched. The purpose of this study was to quantitatively explore the impacts of various I4.0 technologies on CE practices.

A mixed method consisting of a systematic literature review, content analysis, and social network analysis was adopted. First, 266 articles were selected and mined for contents of I4.0 technologies and CE practices; 27 I4.0 technologies and 21 CE practices were identified. Second, 62 articles were found that prove the positive influence of I4.0 technologies on CE practices, and 124 relationships were identified. Third, based on evidence supporting the link between I4.0 technologies and CE practices, a two-mode network and two one-mode networks were constructed, and their network density and degree centrality indicators were analyzed.

I4.0 technologies have a low application scope and degree for promoting CE. The adoption of a single I4.0 technology has limited effect on CE practices, and wider benefits can be realized through integrating I4.0 technologies. The Internet of Things (IoT), additive manufacturing, big data and analytics, and artificial intelligence (AI) are among the top technologies promoting CE implementation and reduction and recycling were identified as the main mechanism. The integration of these technologies is the most popular and effective. Twelve CE practices were identified to be the most widely implemented and supported by I4.0 technologies.

First, only journal articles, reviews, and online publications written in English were selected, excluding articles published in other languages. Therefore, the results obtained only represent a specific group of scholars, which may be fragmented to a certain extent. Second, because the extraction of the impact of I4.0 on CE mainly relies on a manual literature review, this paper only provides the statistics of the number of publications involving relationships, while lacking the weight measurement of relationships.

A comprehensive, quantitative, and visual analysis method was employed to unveil the current implementation levels of I4.0 technologies and CE practices. Further, it was explored how different I4.0 technologies can affect various CE aspects, how different I4.0 technologies are integrated to promote CE realization, and how various CE practices are implemented simultaneously by I4.0 technologies.

The purpose of this paper is to investigate how performance of linear assets can be analysed and displayed, considering both the technical asset and the user context, to simplify cognitive tasks of planning and decision making.

Linear, or continuous assets, such as roads, railways, electrical grids and pipelines, are large, geographically spread out technical systems. Linear assets are comprised of system, subsystem and component levels. Thus, asset managers are involved with each level of the linear asset; asset management has strategic, tactical and operational levels. A methodology is developed to link together the technical and organisational levels and to measure asset performance considering their spatial extension. Geographical location and time are used as independent variables.

For performance measurement of linear assets, it is found that the spatial extension is an equally generic dimension as time is for technical assets in general. Furthermore, as linear assets actually are combinations of linear and point assets; separate analysis of these assets is a prerequisite. Asset performance has been studied in a case study in terms failures and cost; the results indicate that the methodology visualise poor, as well as good, performance in an easy to interpret manner. Besides, the results indicate that other parameters related to dependability can be presented in a similar way.

This study highlights the importance of including the spatial or geographical extension of linear assets in infrastructure managers’ performance measurement. It is believed that the methodology can make planning and decision making more effective by pointing out improvement areas in technical assets, in a way that is appealing to both technicians and managers.

As infrastructure managers are improving their analysis and visualisation of performance, the public's interest of following the information increases, which in turn contributes to the connection between infrastructure managers and the public.

The presented methodology and case study analysed performance in function of both the technical and organisational levels, including the spatial component. It is believed that the methodology for analysing and visualising performance of linear assets is distinctive.