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The paper proposes a maturity assessment method to measure the state of maintenance practices in a company.

The method assumes that a maintenance department is evaluated in terms of its managerial, organizational and technological capabilities. By its adoption it is possible to analyse the maturity level reached by a company, in order to classify the criticalities in its maintenance processes; a company can also make a benchmark with the best companies of a reference sample.

The paper presents the method as a support to identify the levers to improve the maintenance management system. The method is demonstrated on a company whose maturity is assessed before making a benchmark against a sample of other manufacturing companies located in the Northern Italy.

The paper presents a scoring method for maturity assessment and a procedure to use it in order to identify the criticalities in maintenance processes and to subsequently drive the improvement of the maintenance management system. The paper should be useful both to researchers and maintenance professionals interested in using new methods for long‐term planning in maintenance.

Reconfigurable vibrating screen (RVS) is an innovative beneficiation machine designed at Tshwane University of Technology, Republic of South Africa (RSA); with adjustable screen structure to ensure sorting, sizing and screening of varying mineral particles (sizes and quantities) demanded by the customers in a cost-effective manner through the screen structure geometric transformation. In order to ensure that this machine is optimally maintained and managed when utilized in surface and underground mining industries, there is a need to establish or ascertain the best maintenance practices that would be used in optimally managing the RVS machine using decision making techniques. In view of this, the purpose of this paper is to ascertain the best maintenance practices that would be used to optimally maintain and manage the RVS machine when used in surface and underground mines.

Decision making techniques such as weighted decision matrix (WDM) and analytical hierarchy process (AHP) were used in this research work to establish the best maintenance practice for optimally maintaining and managing the RVS machine using relevant literature survey on maintenance management systems as well as the different maintenance criteria decision indices obtained from different conventional vibrating screen machine manufacturers and maintenance experts.

Based on the results obtained from the WDM analysis, it was anticipated that e-maintenance (e-M) system embedded with diagnosing and prognosing algorithms; with a cumulative weight score of 2.37 is the best maintenance practice for managing the RVS machine when used in surface mines, while AHP with deeper decision making analysis anticipated that the robotic-driven maintenance (RM) system with an important decision criteria; safety, and a cumulative hierarchy score of 28.6 percent, supported by e-M management system with a cumulative hierarchy score of 17.6 percent are the best maintenance mix that could be used in optimally maintaining and managing the RVS machine, when used in a craggy and hazardous underground mining environment.

To this effect, it could be anticipated that e-M management system (endowed with the ability to detect fault on the machine, diagnose and prognose the different subsystems of the RVS machine and ascertain the reconfiguration time and process of the RVS machine in recovering production loss during the maintenance of the machine as well as meeting customers demand, etc.) is the best maintenance practice for optimally maintaining the RVS machine when utilized in surface mines while both e-M management system and RM management system (endowed with the ability to carry out automated maintenance tasks achievement under little or no maintenance manager intervention) are also anticipated as the best customized maintenance practices mix that could be used in optimally maintaining the RVS machine, when used in dangerous and hazardous underground mining environment.

This maintenance management system evaluation and selection for optimal RVS machine functionality will serve as a useful information to different mining machines (and other related machines) maintenance managers, in selecting the best maintenance management system for ensuring optimal functionality, reliability and maintainability of machines used in their industries.

The implementation of smart maintenance (SM) has greatly benefited facility managers, construction project managers and other stakeholders within the built environment. Unfortunately, its actualization for stakeholders in the built environment in the fourth industrial revolution (4IR) era remains a challenge. To reduce the challenge, this study aims at conducting a bibliometric analysis to unearth the critical success factors supporting SM implementation. The future direction and practice of SM in the construction industry were also explored.

A bibliometric approach was adopted for reviewing articles extracted from the Scopus database. Keywords such as (“smart maintenance“) OR (“intelligent maintenance”) OR (“technological maintenance”) OR (“automated maintenance”) OR (“computerized maintenance”) were used to extract articles from the Scopus database. The studies were restricted between 2006 and 2021 to capture the 4IR era. The initial extracted papers were 1,048; however, 288 papers were selected and analysed using VOSviewer software.

The findings revealed that the critical success factors supporting the implementation of SM in the 4IR era are collaboration, digital twin design, energy management system and decentralized data management system. Regarding the future practice of SM in the 4IR era, it was also revealed that SM is possible to evolve into maintenance 4.0. This will support the autonomous maintenance of infrastructures in the built environment.

The use of a single database contributed to the limitation of the findings from this study.

Despite the limitations, the findings of this study contributed to practice and research by providing stakeholders in the built environment with the direction of SM practice.

Stakeholders in the built environment have clamoured to implement SM in the 4IR era. This study provided the critical success factors for adopting SM, guaranteeing the 4IR era. It also provides the research trends and direction of SM practice.

The demand for contracts on assets availability has increased. Recently published papers show that the use of asset health monitoring technologies is being encouraged to improve the asset performance. This is based on reason rather than analysis. This paper aims to understand and assess the effect of different types of business processes for maintenance resource levels on the behaviour of the maintenance operations and asset availability located at different customer locations using different asset monitoring levels.

A discrete event simulation (DES) model was developed to mimic complex maintenance operations with different monitoring levels (reactive, diagnostics, and prognostics). The model was created to understand and assess the influence of resources (labour and spare parts) on a particular maintenance operation. The model was created to represent different levels of asset monitoring to be applied in a case study. Subsequently, different levels of spare parts (ranging from deficient inventory to a plentiful spares inventory) and labour were applied to show the effects of those resources on the asset availability.

This research has found that the DES was able to discern different processes for asset monitoring levels in complex maintenance operations. It also provided numerical evidence about applying such asset monitoring levels and proved that the higher asset monitoring level does not always guarantee higher asset availability.

The developed model is a unique model that can provide the decision makers of maintenance operations with numerical evidence to select an appropriate asset monitoring level based on their particular maintenance operations.

A novel DES model was developed to support maintenance operations decision makers in selecting the appropriate asset monitoring level for their particular operations. This unique approach provides numerical evidence rather than reasoning, and also proves that the higher asset monitoring level does not always guarantee higher asset availability.

Purpose – Flexible system management has brought a concept of flexibility in all spheres including maintenance management. Considerable literature is available on various facets of flexibility management, namely, production, supply chain, day‐to‐day activities, etc.; however, not much literature on flexibility in maintenance is reported. The purpose of this paper is to bridge this gap highlighting various issues involved in flexibility on maintenance. Design/methodology/approach – A situation‐actors‐process (SAP)‐learning‐action‐performance (LAP) model has been applied to understand and analyze the concept of flexibility in maintenance. The paper analyses a case study of ABC, a Government maintenance organization for repair of automobiles in India, to discuss the various issues arising out of maintenance flexibility. Findings – Various issues concerning flexibility in maintenance are: business or corporate philosophy, systems and processes, inventory, manpower, performance measurements and information systems. Research limitations/implications – The concept of flexibility in maintenance has been demonstrated using only two facets of maintenance, i.e. manpower and the repair scope in the case study. Practical implications – The SAP‐LAP model presents the concept of flexibility in maintenance adequately. The concept can be implemented while planning the maintenance in any organization for various issues like inventory stock levels, manpower, repair scope, etc. The technicians may be trained on more than one specialty so that they can easily re‐muster into other streams in case of flexible maintenance environment. Originality/value – This is an original approach to apply the concept of flexibility in the area of maintenance management. The issues affecting maintenance flexibility are identified and future researchers may find these gaps interesting.

This paper proposes the extension of a prognosis process by means of the integration of maintenance alternative impacts in order to develop a maintenance decision‐making tool.

The deployment of this extended prognosis process follows a methodology based both on probabilistic and on event approaches.

The importance of the maintenance function has increased due to its role in keeping and improving the system availability and safety but also the product quality. To support this new role, the maintenance concept has undergone several major developments to lead to proactive considerations mainly based on prognosis process allowing one to select the best maintenance plan to be carried out.

Studies over the last 20 years have indicated that around Europe the direct cost of maintenance is equivalent to between 4 and 8 per cent of total sales turnover. The indirect cost of maintenance is likely to be a similar amount. Thus, in the countries where modern maintenance practices have yet to be well adopted by industry, the potential savings from modern maintenance are massive. These modern and efficient maintenances imply identifying the root‐cause of component failures, reducing the failures of production systems, eliminating costly unscheduled shutdown maintenances, and improving productivity as well as quality. It means, for the companies, migrating from their traditional reactive approach, which is “fail and fix”, to “predict and prevent”. The advantage of the latter is that maintenance is performed only when a certain level of equipment deterioration occurs. This “proactive” maintenance is mainly based on prognosis process often considered as the Achilles heel, while its goal is fundamental for implementing anticipation capabilities. This paper looks into this issue by proposing the development of an innovative prognosis process integrating the modelling of maintenance actions and their impacts on system performances. It leads to offering a maintenance aided decision‐making tool cable of assisting the decision‐maker in selecting the best maintenance plan to be carried out.

The feasibility of this new prognosis is experimented on the manufacturing Tele‐Maintenance (TELMA) platform supporting the unwinding of metal bobbins.

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.

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.

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.

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.

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.

Immigrants are important contributors to workplaces, but HRM scholars have only recently begun to study them systematically. We document the prevalence and cross-national variation in populations of immigrant employees. Going beyond a treatment that considers them as another element of diversity, we propose how gradients of status at each level of country, organization, and work group admittance can result in unique outcomes for immigrants who are equally (dis)similar. We offer a taxonomy of immigrant pathways into their destination countries to explore the status hierarchies they are assigned by governments and reinforced by organizations. We provide insights into the ascribed status of immigrants and develop a typology of individual and organizational acculturation strategies based on the cultural tightness and looseness of the destination and origin cultures. We then describe how the reactions of members of an immigrant employee’s social environment are sensitive to ascribed status and cultural tightness-looseness. We do so in a three-stage process that begins with immigrant categorization, followed by conferral of (il)legitimacy, and finally brought together with perceptions of outcome interdependence. Finally, we offer ideas about HRM interventions to guide management scholars in their quest for understanding and improve the experiences of immigrants in the workplace.

Thie purpose of this paper is to present the critical success factors (CSFs) for engaging in the building maintenance business in Hong Kong where maintenance is a major market sector.

In this study, CSFs are identified for the business of building maintenance based on data collected from a questionnaire survey and interviews.

A total of 12 CSFs are identified, such as client's satisfaction, certification of company, reliability of service, quality of service, and company reputation, and most are related to two principal factors, namely maintenance service and organization, and project management.

This paper provides a review of building maintenance in Hong Kong and identifies a list of success factors for the business of building maintenance. The identified CSFs and principal factors provide useful reference for maintenance contractors to have a clear understanding of the expectations of the building maintenance market in Hong Kong.

This paper presents a concept for digitalised maintenance (DM), maps the conceptualised DM to maintenance problems in industries and highlights challenges that might be faced when realizing this concept.

First, maintenance problems that are faced by the industry are presented, followed by a conceptualisation of DM. Next, a typical operational scenario is used as an exemplification to show system dynamics. The characteristics of this conceptualised DM are then mapped to the identified maintenance problems of industry. Then, interesting initiatives in this domain are highlighted, and finally, the challenges to realize this approach are discussed.

This paper identified a set of problems related to maintenance in industry. In order to solve current industrial problems, exploit emerging digital technologies and elevate future industries, it will be necessary to develop new maintenance approaches. The mapping between the criteria of DM and maintenance problems shows the potential of this concept and gives a reason to examine it empirically in future work.

This paper aims to help maintenance professionals from both academia and industry to understand and reflect on the problems related to maintenance, as well as to comprehend the requirements of a digitalised maintenance and challenges that may arise.