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The purpose of this paper is to develop a multifaceted perspective on e-maintenance research and practice over 12 years from 2002 to 2013.

A qualitative research approach is conducted through analysing e-maintenance literature published in peer-review journals from 2002 to 2013 in operations management, information systems, computer science and engineering disciplines.

A multifaceted perspective that reflects evolutionary, managerial, and technological domains of e-maintenance research has been emerged and explained. In addition, stages of e-maintenance process (i.e. integration, aggregation, and prediction) tend to synchronize with organizational levels (i.e. strategic, tactical, and operational) and stimulate the value of e-maintenance practices across the enterprise. However, there are many managerial and technological challenges that inhibit successful implementation of e-maintenance system.

The present research offers managers and vendors a frame of reference that facilitates e-maintenance adoption and implementation. In addition, there is a need for theoretical as well as empirical research in the future to validate the multifaceted perspective in the present study and to obtain more insight into the nature of e-maintenance issues in various settings.

The present paper is one of the first attempts to bridge the gaps in a currently cluttered field of e-maintenance research. It also provides both academics and practitioners with a useful framework that sustains rigorous e-maintenance research and practice.

The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the earlier scattered research in the field, and second, to present a conceptual approach for addressing these challenges in practice.

The study is realized as a combination of a literature review and by the means of analyzing the practices on an industry leader in manufacturing and maintenance services.

This research provides a general understanding over data management challenges in e-maintenance and summarizes their associated proposed solutions. In addition, this paper lists and exemplifies different types and sources of data which can be collected in e-maintenance, across different organizational levels. Analyzing the data management practices of an e-maintenance industry leader provides a conceptual approach to address identified challenges in practice.

Since this paper is based on studying the practices of a single company, it might be limited to generalize the results. Future research topics can focus on each of mentioned data management challenges and also validate the applicability of presented model in other companies and industries.

Understanding the e-maintenance-related challenges helps maintenance managers and other involved stakeholders in e-maintenance systems to better solve the challenges.

The so-far literature on e-maintenance has been studied with narrow focus to data and data management in e-maintenance appears as one of the less studied topics in the literature. This research paper contributes to e-maintenance by highlighting the deficiencies of the discussion surrounding the perspectives of data management in e-maintenance by studying all common data management challenges and listing different types of data which need to be acquired in e-maintenance systems.

The purpose of this paper is to propose a methodology for the engineering of E-maintenance platforms that is based on a value-driven approach.

The methodology assumes that a value-driven engineering approach would help foster technological innovation for maintenance management. Indeed, value-driven engineering could be easily adopted at the business level, with subsequent positive effects on the industrial applications of new information and communication technologies solutions.

The methodology combines a value-driven approach with the engineering in the maintenance scope. The methodology is tested in a manufacturing case to prove its potential to support the engineering of E-maintenance solutions. In particular, the case study concerns the investment in E-maintenance solutions developed in the framework of a Supervisory Control and Data Acquisition system originally implemented for production purposes.

Based on literature research, the paper presents a methodology that is implemented considering three different approaches (business theories, value-driven engineering and maintenance management). The combination of these approaches is novel and overcomes the traditional view of maintenance as an issue evaluated from a cost-benefit perspective.

The purpose of this paper is to presents the current and prospective state of affairs when it comes to the information and communication technologies (ICTs) in condition monitoring (CM) and maintenance, especially for the e-maintenance approach.

The author presents some of the standards for the domain of interest, such as the open system architecture condition-based maintenance. In addition, the e-maintenance approach is gone through as well as such ICTs as, for instance, the emergent web technologies, the service-oriented architecture (SOA), the web services and the Web 2.0 are analysed.

The findings highlight the need for a clearer understanding of the characteristics of different ICTs, such as Web 2.0 technologies, Cloud computing, agent technologies, etc., to be able to use them in an optimal manner for various purposes in the e-maintenance applications. In addition, the standardisation of the emergent ICTs different aspects is shown to be an important factor for the development of different phases of software as well as for its overall acceptance.

The given work presents the current and emergent ICTs for the domain of interest and provides the discussion and various issues connected to these ICTs.

The author provides practical implications of the different ICTs mentioned in the paper, i.e. benefits and possibilities as well as risks when those technologies are implemented for CM and maintenance, especially for the e-maintenance.

The paper provides insight into various current and prospective ICTs for the domain of interest that provides important knowledge for different employees with the objective of a purchase, users of the system, such as technicians, maintenance engineers as well as developers of these systems. Consequently, the paper provides knowledge of different characteristics of the current and prospective technologies, which is important to take into account in order to be able not only to use them in an optimal manner, but also to understand possible constraints if they are used in the system and in applications in the domain.

The purpose of this paper is to describe aspects of content sharing within e‐maintenance, with a view to merging the two areas of maintenance and ICT in a content management perspective.

The approach is an explorative literature study covering aspects of ICT. The analysis is founded on theories related to maintenance and maintenance support. The conclusions of the study are corroborated by experiences from earlier software development and testing.

Most existing contributions to the e‐maintenance debate seem to suffer from too wide a gap between data processing and knowledge management. This tendency can be due to too great a focus on data collection, without any clear identification of the stakeholders' requirements. Hence, a mature e‐maintenance solution should focus on the enhancement of service‐oriented information logistics based on content sharing for an output‐based information strategy.

This study focuses on the needs of content format and transformation content, which includes data format, data structures and data type for objects that are relevant for the maintenance process. Hence, further research could include aspects of infrastructure and service architecture, which are on a higher level of an e‐maintenance solution.

The paper contributes with knowledge that supports decisions about content format in the development of an e‐maintenance solution. This can in turn support a reduction of maintenance‐related hazards through the improved use of ICT.

This paper describes the importance of content management within the e‐maintenance approach. Hence, the paper has implications for both practitioners and researchers as described above.

The purpose of this paper is to demonstrate industrial Internet of Things (IIoT) solution to improve the equipment condition monitoring with equipment status data and process condition monitoring with plasma optical emission spectroscopy data, simultaneously. The suggested research contributes e-maintenance capability by remote monitoring in real time.

Semiconductor processing equipment consists of more than a thousand of components, and unreliable condition of equipment parts leads to the failure of wafer production. This study presents a web-based remote monitoring system for physical vapor deposition (PVD) systems using programmable logic controller (PLC) and Modbus protocol. A method of obtaining electron temperature and electron density in plasma through optical emission spectroscopy (OES) is proposed to monitor the plasma process. Through this system, parts that affect equipment and processes can be controlled and properly managed. It is certainly beneficial to improve the manufacturing yield by reducing errors from equipment parts.

A web-based remote monitoring system provides much of benefits to equipment engineers to provide equipment data for the equipment maintenance even though they are physically away from the equipment side. The usefulness of IIoT for the e-maintenance in semiconductor manufacturing domain with the in situ monitoring of plasma parameters is convinced. The authors found the average electron temperature gradually with the increase of Ar carrier gas flow due to the increased atomic collisions in PVD process. The large amount of carrier gas flow, in this experimental case, was 90 sccm, dramatically decreasing the electron temperature, which represents kinetic energy of electrons.

Semiconductor industries require high level of data security for the protection of their intellectual properties, and it also falls into equipment operational condition; however, data security through the Internet communication is not considered in this research, but it is already existing technology to be easily adopted by add-on feature.

The findings indicate that crucial equipment parameters are the amount of carrier gas flow rate and chamber pressure among the many equipment parameters, and they also affect plasma parameters of electron temperature and electron density, which directly affect the quality of metal deposition process result on wafer. Increasing the gas flow rate beyond a certain limit can yield the electron temperature loss to have undesired process result.

Several research studies on data mining with semiconductor equipment data have been suggested in semiconductor data mining domain, but the actual demonstration of the data acquisition system with real-time plasma monitoring data has not been reported. The suggested research is also valuable in terms of high cost and complicated equipment manufacturing.

The purpose of this paper is to investigate the failure-driven capacity consumption of wheels on the track, to determine whether there are some relations to vehicle wheel configurations that show a larger amount of failures, and to ascertain the influence of the temperature and the travelling direction of the train on the number of events. This information can be used to develop prognostic health management so that more track capacity can be gained without modifications, re-building or re-investments.

This paper presents a study of 1,509 warning and alarm events concerning train wheels. The data come from the infrastructure manager's wheel defect detectors and wheel profile measurement system. These data have been analysed and processed to find patterns and connections to different vehicles, travelling directions and temperatures.

Lower temperatures increase the probability of wheels having high vertical forces. Trains with different wheel configurations show different results. With high vertical forces, the probability of wheel failures at axles 6 and 7 is high for locomotives with two bogies and three axles in each bogie (2×3). All these findings can be used to develop the maintenance, monitoring and inspection principles for wheels.

The inspection of wheels to detect failures needs to be more frequent on days and in seasons with lower temperatures. The wheel inspection should be performed more frequently at axles 6 and 7 for locomotives with a 2×3 wheel configuration. The inspection and monitoring of wheels need to be carried out more carefully for trains travelling south, to avoid a large amount of wheels with high force levels rolling in the southern direction.

The analysis carried out in this paper identifies important factors that correlate with the high occurrence of wheel defects. It also proposes a conceptual e-maintenance model for the combination of wheel condition monitoring data from different system. The value of this study is the provision of information to support prognostic and health management system to support proactive maintenance.

The purpose of this paper is to provide an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition‐based maintenance, reliability‐centred maintenance, e‐maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.

A state‐of‐the‐art literature review has been carried out to answer the following two research questions. First, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Second, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?

The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value‐based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.

A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.

Centrifugal compressors are integral components in oil industry, thus effective maintenance is required. Condition-based maintenance and prognostics and health management (CBM/PHM) have been gaining popularity. CBM/PHM can also be performed remotely leading to e-maintenance. Its success depends on the quality of the data used for analysis and decision making. A major issue associated with it is the missing data. Their presence may compromise the information within a set, causing bias or misleading results. Addressing this matter is crucial. The purpose of this paper is to review and compare the most widely used imputation techniques in a case study using condition monitoring measurements from an operational industrial centrifugal compressor.

Brief overview and comparison of most widely used imputation techniques using a complete set with artificial missing values. They were tested regarding the effects of the amount, the location within the set and the variable containing the missing values.

Univariate and multivariate imputation techniques were compared, with the latter offering the smallest error levels. They seemed unaffected by the amount or location of the missing data although they were affected by the variable containing them.

During the analysis, it was assumed that at any time only one variable contained missing data. Further research is still required to address this point.

This study can serve as a guide for selecting the appropriate imputation method for missing values in centrifugal compressor condition monitoring data.

The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM.

Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed.

In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified.

The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required.

The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.