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The United Nations' Sustainable Development Goal of ensuring healthy lives and promoting well-being for people of all ages underscores the vital role of public healthcare facilities (PHFs) in delivering essential healthcare services. However, these facilities often suffer from inadequate maintenance, exacerbated by the insufficient implementation of maintenance strategies. Recognizing the importance of PHFs in enhancing healthcare services, this paper investigates the Critical Success Factors (CSFs) in the maintenance strategies of PHFs in South Africa.

Through semi-structured interviews with nineteen purposively selected maintenance personnel from the Limpopo Department of Health (DoH), this study identified and analyzed the CSFs to enhance maintenance operations in PHFs. Thematic content analysis was employed to derive key insights from the collected data.

The study's findings highlight adequate maintenance planning and effective leadership as the two overarching CSFs in the maintenance of PHFs. These factors play a pivotal role in addressing challenges that hinder the current maintenance team from meeting maintenance requirements to the satisfaction of both staff and patients within PHFs.

The study offers valuable insights for policymakers to improve the effectiveness of maintenance operations in PHFs. By addressing the identified CSFs, policymakers can enhance maintenance operations in PHFs, positively impacting healthcare service delivery and the well-being of both staff and patients.

This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.

The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.

The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.

This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.

Certified and non-certified organisations must make strategic decisions regarding ISO 9001 adoption, maintenance, renewal and abandonment. However, the ISO 9001 literature lacks a typology of the strategic options available to these organisations. The purpose of this conceptual study is to develop a framework of the alternative strategies for the stages of the ISO 9001 life cycle (implementation/certification, certification maintenance and recertification/decertification stages).

The research method is based on literature review, selection of relevant variables and synthesis of coherent alternative strategies.

Results include the main variables of relevance for the definition of the ISO 9001 strategies (e.g. life cycle stage, organisational motivations, barriers, benefits, internalisation degree and quality of the certification body), the main situations in which organisations can find themselves (in terms of ISO 9001 certification, maintenance and decertification), the strategic options for each situation (e.g.: certify, maintain certification, try harder, change certification body, intensify learning and experimentation with ISO 9001) and the implications and consequences of such options. Research results are integrated into a strategy framework, composed of three strategy matrices, one for each stage of the life cycle. The matrices present the strategic situations, available strategic alternatives and benefits of the strategies.

This study combines the results of previous research to develop an original strategy framework, which constitutes the main research contribution. As far as the author is aware, there is no such strategy framework in the literature. The framework has relevant implications for theory and practice and helps to identify future research directions.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.

The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.

The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.

The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).

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.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

Compared to low-rise and mid-rise buildings, commercial high-rise buildings have severe maintenance management deficiencies due to the complex nature of the structure and building services incorporated. Previous studies have shown that implementing lean in maintenance is a recognised prominent strategy to enhance maintenance performance. Thus, this study aims to investigate how lean maintenance can be applied to improve maintenance management in commercial high-rise buildings in Sri Lanka.

This study adopted a case study method. Three commercial high-rise buildings were selected to conduct the empirical study. An expert survey is also conducted to validate the findings.

The findings of the study revealed that out of the eight cardinal types of lean maintenance waste, six are rooted in the selected cases: (i) excessive preventive maintenance, (ii) waiting (maintenance resources, tools, procuring of additional supplies and documentation and permits), (iii) transportation due to centralised maintenance, (iv) poor inventory management, (v) poor information handling and (vi) poor utilisation of labour. Then the study revealed strategies to eradicate identified lean maintenance wastes.

The findings of this study can be used to guide maintenance practitioners in implementing lean maintenance in Sri Lankan commercial high-rise buildings. Furthermore, the proposed strategies can be directly applied to mitigate identified maintenance wastes.

This paper provides information on how high-rise commercial buildings in Sri Lanka can enhance their maintenance management by mitigating lean maintenance wastes.

Maintenance policy is an element of building maintenance management that deals with organisation policy, planning and procedures, and delineates how maintenance units in an organisation will manage specific building components, auxiliary facilities and services. Given this contextual setting, this study investigates whether organisational maintenance policies (OMPs) utilised in developed countries are relevant in developing countries – using Nigeria as a case study exemplar.

An empirical research design (using deductive reasoning) was implemented for this research. Specifically, a Delphi study conducted revealed 23 elements that impact OMP development in Nigeria.

Of these twenty elements, six had a very high impact on maintenance management (VHI: 9.00–10.00), nine variables had a high impact (HI: 7.00–8.99) and eight other variables scored a medium impact (MI: 5.00–6.99). Emergent findings reveal that the elements of organisational maintenance policy that engender effective building maintenance management include preparation of safety procedure, optimisation of the maintenance policy, optimisation of the maintenance action plan, well-defined priority system, risk factor establishment, suitable maintenance procedures and a clearly delineated process.

The study findings will guide policymakers in identifying the main elements required in maintenance policies development towards making national public asset preservation and economic gains. Also, the content of the future educational curriculum on maintenance management study will be more receptive to the body of knowledge and the built environment industry.

Cumulatively, the research presented illustrates that these elements replicate those adopted in other countries and that effective maintenance management of public buildings is assured when these elements are integral to the development of an OMP.

Asset maintenance in manufacturing industries is a critical issue as organizations are highly sensitive towards maximizing asset uptime. In the advent of Industry 4.0, maintenance is increasingly becoming technology driven and is being termed as Maintenance 4.0. Several barriers impede the implementation of Maintenance 4.0. This article aims at - exploring the barriers to implementation of Maintenance 4.0 in manufacturing industries, categorizing them, analysing them to prioritize and suggesting the digital technologies to overcome them.

Twenty barriers to the implementation of Maintenance 4.0 were identified through literature survey and discussion with the industry experts. The identified barriers were divided into five categories based on their source of occurrence and prioritized using fuzzy-technique for order preference by similarity to ideal solution (TOPSIS), sensitivity analysis was carried out to check the robustness of the solution.

“Data security issues” has been ranked as the most influencing barrier towards the implementation of Maintenance 4.0, whereas “lack of skilled engineers and data scientists” is the least influencing barrier that impacts the implementation of Maintenance 4.0 in the manufacwturing industries.

The outcomes of this research will help manufacturing industries, maintenance engineers/managers, policymakers, and industry professionals for detailed understanding of barriers and identify easy pickings while implementing Maintenance 4.0.

Manufacturing industries are witnessing a paradigm shift due to digitization and maintenance 4.0 forms the cornerstone. Little research has been carried in Maintenance 4.0 and its implementation; this article will help in bridging the gap. The prioritization of the barriers and digital course of actions to overcome those is a unique contribution of this article.