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The purpose of this paper is to create a framework to provide a scalable maintenance program for unmanned aircraft systems (UAS) in order to choose the most suitable and feasible maintenance strategy in terms of reliability.

The paper opted for a reliability-centered maintenance-based approach to develop the framework using a UAS as the starting point of the research. A linear and user-friendly design of the methodology based on a Boolean flowchart was chosen in order to lead the analyst through the process avoiding as much as possible subjectivity decision-making issues. Finally, the framework was, on the component level, performed by a UAS company gathering feedback on its applicability.

An agile and structured decision-making framework for developing scalable maintenance program of UAS is provided. The proposed solution gives the opportunity to tailor the maintenance strategy to the technical characteristics, considering not only the single component but also situations and conditions in which the machine will operate.

Because of the chosen research approach, the framework is potentially applicable to every UAS. A first trial of the method was run on a multirotor vehicle equipped with eight electric brushless motors. Further studies focused on different UAS will be mandatory in order to obtain comparable and robust findings and a reliable approach.

This study offers a different scheme to elaborate a specific maintenance solution related to the characteristics of the system. It strives to remedy the drawbacks of the traditional approach for a manned aircraft not completely suitable for systems with such different functions, features and tasks. The authors believe that the method presented in this paper will provide a new selection tool for choosing maintenance actions based on the features of the UAS.

This paper provides a new and usable solution to include the maintenance actions in the management of pioneering products. In spite of the maintenance program representing an essential aspect to provide reliable assets, frameworks to create programs and to help manufacturers and users are still difficult to find or to apply to different UAS. This gap enhances the misunderstanding that the maintenance is not required or essential for the unmanned aircrafts management.

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.

Disturbances in terms of major crises such as pandemics, fluctuations in demand and oil price, energy consumption and supply chain can significantly impair the maintenance programs effectiveness and efficiency. Hence, there is an urgent need for an agile asset performance management (AAPM) framework.

This paper's main objective is to design a comprehensive framework for an AAPM system that sustains the desired asset performance by reacting efficiently, quickly and intelligently to the changes in the operating context parameters and asset health conditions. Such a framework is adaptive to changes in scenarios and aims to systematise the decision support process, considering different objectives.

The development of the proposed framework has led to identifying an innovative way of seamless integration between crucial reliability and asset management tools. Also, the methodology implementation is expected to promote the practical use of its reliability tools and enable asset stakeholders to break silo working for clear communication around asset performance.

The implementation of the AAPM framework follows a new approach developed during this research and coined by the authors as the “8S approach.”

The purpose of this paper is to identify the main reasons for spare parts logistics failures and address logistics distribution design in order to achieve the desired level of after-sales maintenance service.

This research is based on an empirical case study on a large corporation providing worldwide with retail banking hardware, software and services. The case study focuses on the automated teller machine (ATM) part of activities, with a focus on the spare parts distribution and after-sales service network in the Eastern Europe.

The proposed network solution of multiple distribution centers with short-cut distance saving approach will enable the case study company to redesign their spare part logistics architecture in order to achieve short response time. Research findings reveal possible spare parts delivery delays and thus the service-level agreement failures with clients in the case study company.

This research covers a particular supply chain environment and identified research gaps. It discusses a time-based responsive logistics problem and develops a conceptual framework that would help researchers to better understand logistics challenges of installed equipment maintenance and after-sales service.

This case study research shows the “big picture” of spare parts logistics challenges as vital part of installed equipment after-sales and maintenance service network, as well as emphasizes how the unique context of a market like Russian Federation can set-up a distribution network efficiently. Strategies applied to handle such service-level failures, reverse logistics aspects of repairable and non-repairable spare parts to such large ATM after-sales service network based on this longitudinal case offer value for similar scale companies.

The after-sale service industry is estimated to contribute over 8 percent to the US GDP. For use in this considerably large service management industry, this article provides verification in the application of decision tree-based machine learning algorithms for optimal maintenance decision-making. The motivation for this research arose from discussions held with a large agricultural equipment manufacturing company interested in increasing the uptime of their expensive machinery and in helping their dealer network.

We propose a general strategy for the design of predictive maintenance systems using machine learning techniques. Then, we present a case study where multiple machine learning algorithms are applied to a particular example situation for an illustration of the proposed strategy and evaluation of its performance.

We found progressive improvements using such machine learning techniques in terms of accuracy in predictions of failure, demonstrating that the proposed strategy is successful.

This approach is scalable to a wide variety of applications to aid in failure prediction. These approaches are generalizable to many systems irrespective of the underlying physics. Even though we focus on decision tree-based machine learning techniques in this study, the general design strategy proposed can be used with all other supervised learning techniques like neural networks, boosting algorithms, support vector machines, and statistical methods.

This approach is applicable to many different types of systems that require maintenance and repair decision-making. A case is provided for a cloud data storage provider. The methods described in the case can be used in any number of systems and industrial applications, making this a very scalable case for industry practitioners. This scalability is possible as the machine learning techniques learn the correspondence between machine conditions and outcome state irrespective of the underlying physics governing the systems.

Sustainable systems and operations require allocating and utilizing resources efficiently and effectively. This approach can help asset managers decide how to sustainably allocate resources by increasing uptime and utilization for expensive equipment.

This is a novel application and case study for decision tree-based machine learning that will aid researchers in developing tools and techniques in this area as well as those working in the artificial intelligence and service management space.

The purpose of this paper is to promote a system dynamics-discrete event simulation (SD-DES) hybrid modelling framework, one that is useful for investigating problems comprising multifaceted elements which interact and evolve over time, such as is found in TPM.

The hybrid modelling framework commences with system observation using field notes which culminate in model conceptualization to structure the problem. Thereafter, an SD-DEShybrid model is designed for the system, and simulated to proffer improvement programmes. The hybrid model emphasises the interactions between key constructs relating to the system, feedback structures and process flow concepts that are the hallmarks of many problems in production. The modelling framework is applied to the TPM operations of a bottling plant where sub-optimal TPM performance was affecting throughput performance.

Simulation results for the case study show that intangible human factors such as worker motivation do not significantly affect TPM performance. What is most critical is ensuring full compliance to routine and scheduled maintenance tasks and coordinating the latter to align with rate of machine defect creation.

The framework was developed with completeness, generality and reuse in view. It remains to be applied to a wide variety of TPM and non-TPM-related problems.

The developed hybrid model is scalable and can fit into an existing discrete event simulation model of a production system. The case study findings indicate where TPM managers should focus their efforts.

The investigation of TPM using SD-DES hybrid modelling is a novelty.

DRIVER embodies a bold vision – that of worldwide networks of scientific data repositories. This paper seeks to examine the aims of the European Union funded project, to explore the development of a distributed infrastructure that enables enhanced interoperability of data, resulting in a global knowledge infrastructure supporting the scholarly communication of the future.

The primary objective of DRIVER was to establish a flexible, robust, and scalable infrastructure for all European and world‐wide digital repositories, managing scientific information in an open access model increasingly demanded by researchers, funding organisations and other stakeholders. Adopting a result‐driven approach, activities focused on the expansion of the content base with high quality research outputs, including textual research papers, data sets and other scholarly publications.

The release of the D‐NET v1.0 open source software proved a successful basis for a distributed service‐oriented architecture, enabling enhanced interoperability of data and service‐providers, and offering wide‐ranging functionality including search; recommendation; collection building, and personal profiling as innovative tools for repository managers. In addition, it was found that in building a robust network of voluntary content providers, known as the DRIVER Confederation, the infrastructure came to support a durable organisational structure, now formally constituted as the Confederation of Open Access Repositories (COAR). The international repository organisation enables further collaboration between research communities in a co‐ordinated network comprising a growing number of institutional repositories, national federations and research institutions and data aggregators.

The development of COAR is the extension of the EU‐based infrastructure to global research communities in China, India, Africa and Latin America, deploying a vigorous awareness and advocacy programme. Evolving from the DRIVER Confederation, COAR aims to provide an ongoing support service for repository managers, in a dynamic set of guidelines aimed at data interoperability, and to provide the strategic support required to implement new forms of scholarly communication. These issues are addressed in terms of technical infrastructure developments but will focus on strategic issues of policy development, improved services and additional functionality offered to the scholarly community.

This paper outlines DRIVER's unique response to the changing global information environment. Concepts of strategic international collaboration are pursued in COAR, based on the scientific and technical collaboration achieved in DRIVER. The paper addresses significant repository development goals that currently challenge repository managers, librarians, scholars and funders and that indicate the future of Open Access publication – in the ultimate goal of a global and interactive representation of human knowledge.

The blockchain-based digital twin has been recognized as a prominent technological ecosystem featuring synergies with both established and emergent information management practice. The purpose of this research is to explore the applicability, interoperability and integrability of a blockchain-based digital twin for asset life cycle management and develop a model of framework which positions the digital twin within a broader context of current management practice and technological availability.

A systematic literature review was performed to map use cases of digital twin, IoT, blockchain and smart contract technologies. Surveys of industry professionals and analyses were conducted focussing on the mapped use cases' life cycle–centric applicability, interoperability and integrability with current asset life cycle management practice, exploring decision support capabilities and industry insights. Lastly, a model of framework was developed based on the use case, interoperability and integrability findings.

The results support approaching digitization initiatives with blockchain-based digital twins and the positioning of the concept as both a strategic tool and a multifunctional on-field support application. Integrability enablers include progression towards BIM level 3, decentralized program hubs, modular cross-technological platform interfaces, as well as mergeable and scalable blockchains.

Knowledge of use cases help highlight the functionality of an integrated technological ecosystem and its connection to comprehensive sets of asset life cycle management aspects. Exploring integrability enablers contribute to the development of management practice and solution development as user expectations and technological prerequisites are interlinked.

The research explores asset life cycle management use cases, interoperability and integrability enablers of blockchain-based digital twins and positions the technological ecosystem within current practice and technological availability.

In Bangladesh, 30 percent of the population lives beyond the “last mile” of traditional distribution networks and serving this rural low‐income population with socially useful goods is a huge challenge. The purpose of this paper is to present one of the most innovative and successful cases of its kind in the world, a social enterprise rural distribution model originally developed by CARE Bangladesh and the Bata Shoe Company, to illustrate the possibility of combining market‐based solutions to poverty with socially responsible business growth.

This in‐depth case study was developed over the course of three field visits to Bangladesh between November 2009 and September 2010 based on 25 face‐to‐face interviews with rural sales women, Bata employees and CARE staff as well as participant observation and review of project documents and media reports.

The case provides insights into the origins, lessons learned and key success factors of viable rural sales agent distribution networks serving the poor. A key tension to be managed is keeping the costs of the network down while ensuring that every member is adequately incentivized.

The 3,000 women sales agents in rural Bangladesh engaged with the Rural Sales Program have benefited from earning viable incomes in contexts where opportunities for employment and empowerment of women are limited. Rural populations have gained affordable access to socially beneficial goods such as fortified foods, seeds, daily necessities and shoes. Companies have benefited from learning how to adapt their product offerings to meet the needs of low‐income customers.

Where rural sales initiatives elsewhere have faced challenges, this case is the first published account of the origins of how CARE, Bata, and other companies established a viable and scalable rural sales agent distribution network for the commercial benefit of companies and the economic and social benefit of poor women and their customers.

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.