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While the petroleum industry remains to be the main source of energy in the world, it is responsible for a large amount of resource consumption, environmental emission and safety issues. In this industry, most of the refinery equipment are running out of their designed life cycle, leading to many challenges regarding equipment reliability, products quality, organizations’ profitability, human resources safety and job satisfaction, and environmental pollution, which affects not only the human resources of the refinery but also the people who live in the vicinity. This study aims to model and simulate the maintenance system of an oil refinery to reduce the rotating equipment’s downtime while simultaneously considering the three pillars of sustainability.

Considering the complexity of the system and its inherent dynamism, System Dynamics (SD) approach is applied to model and simulate the maintenance system of an oil refinery, aiming at reducing equipment’s downtime considering the three pillars of sustainability simultaneously. As a case study, the maintenance system of rotating equipment in the Abadan oil refinery of Iran is investigated.

Individual policies are investigated and categorized into three main groups: economic, social and environmental. The dynamic nature of the system demonstrates that applying combinations of the policies would be more effective than performing individual ones or even a combination of all policies at the same time. The findings show that to manage the maintenance and reliability issues in complex industries, only operational level maintenance strategies would not be helpful; rather, a holistic strategic solution counting different suppliers or even the government policies supporting the operational level maintenance decisions would be effective.

This study is the first which brings the perspective of sustainable policy-making in the SD modeling of a complex maintenance system like that of the petroleum industry. The developed model considers economic, environmental and social objectives simultaneously. Besides, it reflects the role of different stakeholders in the system. Furthermore, the policy-making attempt is not limited to the operational level corrective and maintenance solutions; instead, a comprehensive, holistic view is applied.

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.

The chemical plant (CP) maintenance industry has been under increasing pressure by process designers to demonstrate its evaluation and information management of model checking (MC) on the durability’s performance and design of plant control instrument. This main problem has been termed as imperfect maintenance actions (IMAs) level. Although IMAs have been explored in interdisciplinary maintenance environments, less is known about what imperfect maintenance problems currently exist and what their causes are, such as the recent explosion in the Beirut city (4 August 2020, about 181 fatalities). The aim of this paper is to identify how CP maintenance environments could integrate MC within their processes.

To achieve this aim, a comprehensive literature review of the existing conceptualisation of MC practices is reviewed and the main features of information and communication technology tools and techniques currently being employed on such IMA projects are carried out and synthesised into a conceptual framework for integrating MC in the automation system process.

The literature reveals that various CP designers conceptualise MC in different ways. MC is commonly shaped by long-term compliance to fulfil the requirement for maintaining a comfortable durability risk on imperfect maintenance schemes of CP projects. Also, there is a lack of common approaches for integrating the delivery process of MC. The conceptual framework demonstrates the importance of early integration of MC in the design phase to identify alternative methods to cogenerate, monitor and optimise MC.

Thus far, this study advances the knowledge about how CP maintenance environments can ensure MC delivery. This paper highlights the need for further research to integrate MC in CP maintenance environments. A future study could validate the framework across the design phase with different CP project designers.

The purpose of this paper is to propose an improved multi-objective optimization model for the condition-based maintenance (CBM) of single-component systems which considers periodic imperfect maintenance and ecological factors.

Based on the application of non-periodic preventive CBM, two recursion models are built for the system: hazard rate and the environmental degradation factor. This paper also established an optimal multi-objective model with a normalization process. The multiple-attribute value theory is used to obtain the optimal preventive maintenance (PM) interval. The simulation and sensitivity analyses are applied to obtain further rules.

An increase in the number of the occurrences could shorten the duration of a maintenance cycle. The maintenance techniques and maintenance efficiency could be improved by increasing system availability, reducing cost rate and improving degraded condition.

In reality, a variety of environmental situations may occur subsequent to the operations of an advanced manufacturing system. This model could be applied in real cases to help the manufacturers better discover the optimal maintenance cycle with minimized cost and degraded condition of the environment, helping the corporations better fulfill their CSR as well.

Previous research on single-component condition-based predictive maintenance usually focused on the maintenance costs and availability of a system, while ignoring the possible pollution from system operations. This paper proposed a modified multi-objective optimization model considering environment influence which could more comprehensively analyze the factors affecting PM interval.

There is widespread and long-lasting worry related to the condition of public purpose buildings and public investments. Public buildings make up a huge capital stock and proper maintenance and investments are important for public policy. Notwithstanding, the relevant research literature is fragmented and spread across several fields. The authors take stock of earlier and more recent research and suggest some ideas for future research.

The authors summarize the relevant literature and discuss implications of various theoretical assumptions and empirical findings for maintenance and investment strategies.

A better understanding of the role of public facilities in public service provision is important. Relevant topics for further research are the impact of technological changes, both in buildings and service provision, economic issues including macroeconomic shocks and trends that influence public funding and demand for public services, and advancing maintenance scheduling models to consider a portfolio of facilities. Further, the empirical literature suffers from a lack of relevant data to gauge both the condition of public facilities and their impact on public services.

There is widespread worry that poor facilities adversely impact public services, but the size and significance of this impact are an open question. This paper contributes by taking stock of the existing research on public facilities, maintenance, and investments, and suggest ideas for further work.

Unmanned aircraft applications are quickly expanded in different fields. These systems are complex that include several subsystems with different types of technologies. Maintenance and inspection planning is necessary to obtain optimal performance and effectiveness. The failure rate in these systems is more than commercial and manned aircraft since they are usually cheaper. But maintenance and operation planning are difficult because we deal with a system that has multi-components, multi-failure models, and different dependencies between subsystems without any advanced health monitoring system. In this paper, this matter is considered and a framework to determine optimal maintenance and inspection plan for this type of system is proposed to improve system reliability and availability. The new criteria according to this field are proposed.

Maintenance of unmanned systems influences their readiness; also, according to the complexity of the system and different types of components, maintenance programming is a vital requirement. The plan should consider several criteria and disciplines; thus, multicriteria decision approaches may be useful. On another side, the reliability and safety of unmanned aircraft are the most important requirements in the design and operation phases. The authors consider these parameters and develop a framework based on risk-based maintenance to overcome the problems for unmanned systems. This framework consists of two stages: at the first stage, the critical components and failure modes are determined by FMEA, and in the second stage, the priority of maintenance tasks is determined by a fuzzy multicriteria weighted decision system. In this study, fourteen criteria with different levels of importance are developed and proposed to find the best plan for maintenance and inspection intervals. These criteria have been extracted from the literature review, the author's experience, and expert opinions.

A novel framework for risk-based maintenance has been proposed. Risk determination and risk criteria are the most important factors in this framework. Risks are determined by FMEA, and new criteria are proposed that are used for decision-making. These criteria are proposed based on practical experience and experts' opinions for the maintenance process in the aeronautic industry. These are evaluated by industrial cases, and this framework capability has been demonstrated.

The proposed framework and criteria for small unmanned aircraft have been developed based on a practical point of view and expert opinion. Thus for implementation in other aeronautic industries, the framework may need a minor modification.

Two important subsystems of an unmanned aircraft have been studied, and the capabilities of this method have been presented.

This research is original work to determine a maintenance program for unmanned aircraft that their application has rapidly grown up. Practical and design parameters have been considered in this work.

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.

The state of public buildings in Tanzania exhibits evidence of a lack of maintenance and repair. Despite efforts to raise the performance of public buildings, little emphasis is placed on maintenance works and related factors affecting maintenance costs of public buildings, which are often high. This study aims to examine factors affecting maintenance costs of public buildings.

This was a case study involving two government building agencies – Tanzania Buildings Agency (TBA) and National Housing Corporation (NHC). A total of 387 tenants and 29 experts participated in the study. Data were collected using questionnaires and analyzed using Stata version 16 – descriptive statistics feature reporting absolute numbers and frequencies.

Both tenants and experts ranked building age, poor quality control, building material used, execution of work when it is urgent and inadequate financial resources as major factors affecting maintenance costs of public buildings. In the distinctive rating, tenants ranked resource management as a major factor, while experts ranked ignorance about the property of materials, misuse of buildings and faulty maintenance as major factors.

The study has some limitations such as geographical coverage which is limited to Dar es Salaam and Dodoma regions, hence missing information from other regions may have different experiences. Additionally, data were collected in a self-reported manner which could bring about information bias.

Findings of this study provide an insight on recent developments on the factors affecting maintenance cost of buildings using two cases of NHC and TBA which are single entities owning a substantial amount of housing units in Tanzania. Factors affecting the maintenance cost of public buildings identified in this study is a threshold for experts to devise strategies for minimizing maintenance costs.

To the best of the authors’ knowledge, this is the first study that assessed factors affecting maintenance cost in public buildings run by TBA and NHC from the tenant and expert perspectives.

With the irresistible growth in digitization, data backup policies become essential more than ever for organizations seeking to improve reliability and availability of organizations' information systems. However, since backup operations do not come free, there is a need for a data-informed policy to decide how often and which type of backups should be taken. In this paper, the authors present a comprehensive mathematical framework to explore the design space for backup policies and to optimize backup type and interval in a given system. In the authors' framework, three separate cost factors related to the backup process are identified: backup cost, recovery cost and data loss cost. The objective function has a multi-criteria structure leading to a backup policy minimizing a weighed function of these factors. To formalize the cost and objective functions, the authors get help from renewal theory in reliability modeling. The authors' optimization framework also formulates mixed policies involving both full and incremental backups. Through numerical examples, the authors show how the authors' optimization framework could facilitate cost-saving backup policies.

The methodology starts with designing different backup policies based on system parameters. Each constructed policy is optimized in terms of backup period using renewal theory. After selecting the best back-up policy, the results are demonstrated through numerical studies.

Data backup polices that are tailored to system parameters can result in significant gains for IT (Information Technology) systems. Collecting the necessary parameters to design intelligent backup policies can also help managers understand managers' systems better. Designed policies not only provides the frequency of back up operations, but also the type of backups.

The original contribution of this study is the explicit construction and determination of the best backup policies for IT systems that are prone to failure. By applying renewal theory in reliability, the authors present a mathematical framework for the joint optimization of backup cost factors, i.e. backup cost, recovery time cost and data loss cost.

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).