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The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

A key factor adversely affecting contractor social networking performance is the improper handling and information management of contractor’s services delivery on websites. Contractor social networking is particularly problematic on industrialised building system (IBS) infrastructure maintenance projects where contractor’s certified quality product and firms are not matched with maintenance specialisation services. The paper aims to discuss this issue.

This paper reports on the early stages of research which is developing a new information and communications technology (ICT)-based approach to managing contractor social networking on IBS infrastructure maintenance schemes. As a precursor to this work, the paper reviews current contractor social networking websites practices on IBS infrastructure maintenance projects and explores the ICT tools and techniques currently being employed on such projects.

The findings reveal the need for more sophisticated contractor social networking websites solutions which accord with the needs of IBS infrastructure maintenance schemes.

The paper concludes by presenting a research framework for developing such a system in the future.

The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.

An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.

The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.

Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.

Inadequate strategic planning and maintenance budget may undermine the maintenance of the Higher Education Institution Building (HEIB). Studies have shown that a customised maintenance concept such as Soft System Methodology (SSM) can improve public building maintenance operations. There is a paucity of studies regarding public HEIB maintenance in Nigeria via an SSM approach. Therefore, the research investigated the state of public HEIB and developed a framework to improve public HEIB maintenance practices in Nigeria.

The research adopted SSM to understand Nigeria’s public HEIB maintenance practices. The SSM permitted a substitute approach to improve public HEIB maintenance practices via a developed framework. Data were collated via virtual interviews with experts, and findings were presented in line with the SSM seven steps.

Findings show that besides the shoddy state of public HEIB maintenance, there is no public digitalised HEIB framework to improve maintenance practices across Nigeria’s higher education institutions. The study developed a digitalised framework with the support of Computerised Maintenance Management System from the findings. It would reposition the public HEIB and stir up various agencies/departments/units managing maintenance for better service delivery via integrated delivery, practical, methodological and managerial aspects.

The research investigated Nigeria’s public HEIB maintenance practices via SSM to identify the required document and propose a feasible framework to improve Nigeria’s HEIB maintenance practices. Besides the developed conceptual framework, Nigeria’s HEIB maintenance practitioners and higher institution chief executives can use the recommended framework as guidelines to improve HEIB maintenance practices.

A common understanding of what events to regard as production disturbances (PD) are essential for effective handling of PDs. Therefore, the purpose of this paper is to answer the two questions: how are individuals with production or maintenance management positions in industry classifying different PD factors? Which factors are being measured and registered as PDs in the companies monitoring systems?

A longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data were collected from 80 companies in 2001 using a paper-based questionnaire, and from 71 companies in 2014 using a web-based questionnaire.

A diverging view of 21 proposed PD factors is found between respondents in manufacturing industry, and there is also a lack of correspondence with existing literature. In particular, planned events are not classified and registered to the same extent as downtime losses. Moreover, the respondents are often prone to classify factors as PDs compared to what is actually registered. This diverging view has been consistent for over a decade, and hinders companies to develop systematic and effective strategies for handling of PDs.

There has been no in-depth investigation, especially not from a longitudinal perspective, of the personal interpretation of PDs from people who play a central role in achieving high reliability of production systems.

The purpose is to describe new business opportunities within the Swedish railway industry and to support the development of business models that corresponds with the needs and requirements of Industry 4.0, here denoted as Service Management 4.0.

The study is an in-depth and descriptive case study of the Swedish railway system with specific focus on a railway vehicle maintainer. Public reports, statistics, internal documents, interviews and dialogues forms the basis for the empirical findings.

The article describes the complex business environment of the deregulated Swedish railway industry. Main findings are in the form of identified business opportunities and new business model propositions for one of the key actors, a vehicle maintainer.

The article provides valuable understanding of business strategy development within complex business environments and how maintenance related business models could be developed for reaching Service Management 4.0.

Technological advancements are reshaping the manufacturing industry toward digitalized manufacturing. Despite the importance of top-class maintenance in such systems, many industrial companies lack a clear strategy for maintenance in digitalized manufacturing. The purpose of this paper is to facilitate the implementation of maintenance in digitalized manufacturing by proposing a strategy development process for the Smart Maintenance concept.

This study is designed as a multiple-case study, where the strategy development in three industrial cases is analyzed. Several methods were used to collect data on the case companies' development of smart maintenance strategies. The data were analyzed with an inductive approach.

A process of strategy development for smart maintenance is proposed, including six steps: benchmarking, setting clear goals, setting strategic priority, planning key activities, elevating implementation and follow-up.

The proposed process provides industry practitioners with a step-by-step guide for the development of a clear smart maintenance strategy, based on the current state of their maintenance organization. This creates employee engagement and is a new way of developing maintenance strategies.

Maintenance strategies are traditionally regarded as a selection of corrective/reactive and preventive maintenance actions using a top-down approach. By contrast, the proposed process is starting from the current state of the maintenance organization and allows a mixture of top-down and bottom-up approaches, supporting organizational development. This is a rare perspective of maintenance strategies and will make maintenance organizations ready for the demands of digitalized manufacturing.