Augmented Reality (AR) technologies for supporting maintenance operations have been an academic research topic for around 50 years now. In the last decade, major progresses have been made and the AR technology is getting closer to being implemented in industry. In this paper, the advantages and disadvantages of AR have been explored and quantified in terms of Key Performance Indicators (KPI) for industrial maintenance. Unfortunately, some technical issues still prevent AR from being suitable for industrial applications. This paper aims to show, through the results of a systematic literature review, the current state of the art of AR in maintenance and the most relevant technical limitations. The analysis included filtering from a large number of publications to 30 primary studies published between 1997 and 2017. The results indicate a high fragmentation among hardware, software and AR solutions which lead to a high complexity for selecting and developing AR systems. The results of the study show the areas where AR technology still lacks maturity. Future research directions are also proposed encompassing hardware, tracking and user-AR interaction in industrial maintenance is proposed

Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG‐based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG‐based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time‐based, and frequency‐based or time‐frequency‐based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.

Conventionally there is a strong relation between manufacturing and services in complex engineering industries. For companies which aim to last in the competitive manufacturing market choosing appropriate decision making methods to improve their maintenance delivery has a vital role. The aim of this paper is to review Multi Criteria Decision Making (MCDM) models, evaluate each method and do a critical comparison to assess them from a maintenance management point of view. The first section of this paper reviews MCDM methods in different literature, and then the second part develops a set of criteria to classify different techniques. At the end methods are compared based on developed criteria. This paper assesses different MCDM models, and provides a framework to select approaches for maintenance management

“Additive Manufacturing” (AM) is a promising technology which will provide major advantages to Defence Support Service providers, given its ability of delocalised manufacturing near the point of use. The technology is gaining increasing interest due to its disruptive potential. AM groups together a wide range of different approaches which have the ability to convert a 3D file into a physical product by depositing layer upon layer of material. AM is still under development and considered an immature technology. This immaturity provides high level of uncertainty around key indicators such as time and cost. These indicators represent also key decision variables to evaluate AM and compare it with traditional manufacturing. This review paper represents an investigation of existing knowledge on AM and aims to present to the reader the various AM approaches with a detailed focus on the most applicable technologies to Defence Support Services. The paper is structured as follows, firstly the various technologies of AM and their economic aspects are presented, secondly the cost modelling techniques are investigated and finally a discussion is carried out. The contribution of this paper is to present to Defence Support Service stakeholders the various AM technologies and cost modelling techniques for measuring the product or service cost

Current developments in “Wire+Arc Additive Manufacturing” (WAAM) have demonstrated the suitability of the technology for rapid, delocalized and flexible manufacturing. Providing a defence platform with the ability of on-board WAAM capability, would give the platform unique advantages such as improved availability of its systems and ability to recover its capability after being subject to shock. This paper aims to investigate WAAM technology and define a WAAM based manufacturing system for In-platform applications