Study of Augmented Reality based manufacturing for further integration of quality control 4.0: a systematic literature review

Augmented Reality (AR) has gradually become a mainstream technology enabling Industry 4.0 and its maturity has also grown over time. AR has been applied to support different processes on the shop-floor level, such as assembly, maintenance, etc. As various processes in manufacturing require high quality and near-zero error rates to ensure the demands and safety of end-users, AR can also equip operators with immersive interfaces to enhance productivity, accuracy and autonomy in the quality sector. However, there is currently no systematic review paper about AR technology enhancing the quality sector. The purpose of this paper is to conduct a systematic literature review (SLR) to conclude about the emerging interest in using AR as an assisting technology for the quality sector in an industry 4.0 context. Five research questions (RQs), with a set of selection criteria, are predefined to support the objectives of this SLR. In addition, different research databases are used for the paper identification phase following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology to find the answers for the predefined RQs. It is found that, in spite of staying behind the assembly and maintenance sector in terms of AR-based solutions, there is a tendency towards interest in developing and implementing AR-assisted quality applications. There are three main categories of current AR-based solutions for quality sector, which are AR-based apps as a virtual Lean tool, AR-assisted metrology and AR-based solutions for in-line quality control. In this SLR, an AR architecture layer framework has been improved to classify articles into different layers which are finally integrated into a systematic design and development methodology for the development of long-term AR-based solutions for the quality sector in the future

Smart working technologies in industry 4.0 : contributions to different manufacturing activities and workers’ skills

A Indústria 4.0 é considerada a quarta revolução industrial porque utiliza uma ampla integração de tecnologias de informação e de operação na fabricação industrial. Apesar dessa perspectiva tecnológica, diversos estudos vêm evidenciando a importância de considerar o fator humano para o desenvolvimento de um sistema de manufatura inteligente. Nesse sentido, a dimensão denominada como Smart Working precisa ser melhor investigada, uma vez que entender como as tecnologias afetam os trabalhadores e as habilidades desses são cruciais para o bom desempenho das fábricas. Em razão disso, o objetivo desta dissertação foi entender como as Smart Working Technologies (SWT) podem contribuir para as atividades e as habilidades dos trabalhadores da manufatura. Para tanto, primeiramente foi realizada uma análise abrangente da literatura para identificar as SWT e seus impactos nas capacidades dos trabalhadores em suas atividades de manufatura. Deste modo, foram analisados 80 artigos que relacionam as SWT em oito atividades de manufatura. Posteriormente, foi selecionada uma das SWT mais relevantes conforme a literatura, os robôs colaborativos, para identificar os efeitos das tecnologias nas habilidades dos trabalhadores. Deste modo, foram analisados 138 casos de aplicação reportados por uma das empresas fornecedoras líderes mundiais, bem como três entrevistas com empresas adotantes da tecnologia. Os resultados apontam que existem 15 SWT que podem ser implementadas nas atividades de manufatura e relacionadas às capacidades dos trabalhadores. Além disso, os resultados também apontam que podem existir quatro efeitos das SWT nas habilidades dos trabalhadores. Estes achados demonstram que de acordo com a estratégia da empresa uma SWT pode impactar de diferentes formas os trabalhadores.Industry 4.0 is considered the fourth industrial revolution because it uses a broad integration of information and operating technologies in industrial manufacturing. Despite this technological perspective, several studies have highlighted the importance of considering the human factor to develop a smart manufacturing system. In this sense, the Smart Working dimension needs to be further investigated since understanding how technologies affect workers and their skills are crucial for factories' good performance. Therefore, the objective of this dissertation was to understand how Smart Working Technologies (SWT) can contribute to the activities and skills of manufacturing workers. To this end, firstly a systematic literature review was carried out to identify SWTs and their impacts on workers' capabilities in their manufacturing activities. Thus, 80 articles relating to SWT in eight manufacturing activities were analyzed. Subsequently, one of the most relevant SWTs according to the literature, collaborative robots, was selected to identify the effects of technologies on workers' skills. In this way, 138 application cases reported by one of the world's leading supplier companies were analyzed, as well as three interviews with companies that adopted the technology. The results show that there are 15 SWT that can be implemented in manufacturing activities and related to workers' capabilities. In addition, the results also point out that there may be four effects of SWT on workers' skills. According to the company's strategy, these findings demonstrate that an SWT can impact workers in different ways

Deployment of a smart and predictive maintenance system in an industrial case study

Industrial manufacturing environments are often characterized as being stochastic, dynamic and chaotic, being crucial the implementation of proper maintenance strategies to ensure the production efficiency, since the machines? breakdown leads to a degradation of the system performance, causing the loss of productivity and business opportunities. In this context, the use of emergent ICT technologies, such as Internet of Things (IoT), machine learning and augmented reality, allows to develop smart and predictive maintenance systems, contributing for the reduction of unplanned machines? downtime by predicting possible failures and recovering faster when they occur. This paper describes the deployment of a smart and predictive maintenance system in an industrial case study, that considers IoT and machine learning technologies to support the online and real-time data collection and analysis for the earlier detection of machine failures, allowing the visualization, monitoring and schedule of maintenance interventions to mitigate the occurrence of such failures. The deployed system also integrates machine learning and augmented reality technologies to support the technicians during the execution of maintenance interventions.2411-78B2-7CDB | Pedro Miguel MoreiraN/

Potential of mobile applications in human-centric production and logistics management

With the increasing market penetration of smart devices (smartphones, smartwatches, and tablets), various mobile applications (apps) have been developed to fulfill tasks in daily life. Recently, efforts have been made to develop apps to support human operators in industrial work. When apps installed on commercial devices are utilized, tasks that were formerly done purely manually or with the help of investment-intensive specific devices can be performed more efficiently and/or at a lower cost and with reduced errors. Despite their advantages, smart devices have limitations because embedded sensors (e.g., accelerometers) and components (e.g., cameras) are usually designed for nonindustrial use. Hence, validation experiments and case studies for industrial applications are needed to ensure the reliability of app usage. In this study, a systematic literature review was employed to identify the state of knowledge about the use of mobile apps in production and logistics management. The results show how apps can support human centricity based on the enabling technologies and components of smart devices. An outlook for future research and applications is provided, including the need for proper validation studies to ensure the diversity and reliability of apps and more research on psychosocial aspects of human-technology interaction

Anthropocentric perspective of production before and within Industry 4.0

Abstract This paper presents a systematic literature review (SLR) of the anthropocentric perspective of production before and after (or, better, within) Industry 4.0. We identify central research clusters regarding traditional Anthropocentric Production Systems (APS) and Anthropocentric Cyber Physical Production Systems. By comparing the two perspectives, we are able to analyse new emerging paradigms in anthropocentric production caused by Industry 4.0. We further make prediction of the future role of the human operator, his needed knowledge and capabilities and how assistance systems support the Operator 4.0. Our paper gives a brief outlook of current and needed future research. It builds grounds for further scholarly discussion on the role of humans in the factory of the future

Augmented reality in support of intelligent manufacturing – A systematic literature review

Industry increasingly moves towards digitally enabled ‘smart factories’ that utilise the internet of things (IoT) to realise intelligent manufacturing concepts like predictive maintenance or extensive machine to machine communication. A core technology to facilitate human integration in such a system is augmented reality (AR), which provides people with an interface to interact with the digital world of a smart factory. While AR is not ready yet for industrial deployment in some areas, it is already used in others. To provide an overview of research activities concerning AR in certain shop floor operations, a total of 96 relevant papers from 2011 to 2018 are reviewed. This paper presents the state of the art, the current challenges, and future directions of manufacturing related AR research through a systematic literature review and a citation network analysis. The results of this review indicate that the context of research concerning AR gets increasingly broader, especially by addressing challenges when implementing AR solutions.No funding was received

Virtual and augmented reality as enablers for improving the service on distributed assets

The evolution of Augment and Virtual Reality is enabling new solutions. This paper addresses creation of applications to support service and maintenance of distributed systems. Indeed this approach could be applied to devices provided as service for industrial and individual use and could introduce new capabilities in terms of training for operators, control and remote service support. The paper presents a case study devoted to lead the introduction of these innovative solutions in industrial and health care system

Using AR interfaces to support industrial maintenance procedures

Industries are becoming more and more digitized to better implement intelligent and predictive maintenance support systems, aligned with Industry 4.0, which requires the progressive digitization of data collection and processes. Maintenance interventions, in an evolving technological context, are increasingly more complex and difficult for technicians to perform. In these environments, the use of Augmented Reality (AR) to help assist and guide in the maintenance operations, can accomplish a considerable gain in productivity. AR allows to superimpose information objects in real scenes, such as text, images, audiovisuals, and 2D/3D model animations, making available contextual information about the process, based on location and perspective. This paper describes the design and implementation of a prototype augmented reality application to support maintenance tasks inside a metal stamping production unit, that produces components for the automotive sector. It aims to train and guide personnel during the maintenance operations, and offering an extra channel to reach expert help.2411-78B2-7CDB | Pedro Miguel MoreiraN/

Adopting augmented reality in the age of industrial digitalisation

Industrial augmented reality (IAR) is one of the key pillars of the industrial digitalisation concepts, which connects workers with the physical world through overlaying digital information. Augmented reality (AR) market is increasing but still its adoption levels are low in industry. While companies strive to learn and adopt AR, there are chances that they fail in such endeavours due to lack of understanding key challenges and success factors in this space. This study identifies critical success factors and challenges for IAR implementation projects based on field experiments. The broadly used technology, organisation, environment (TOE) framework was used as a theoretical basis for the study, while 22 experiments were conducted for validation. It is found that, while technological aspects are of importance, organisational issues are more relevant for industry, which has not been reflected to the same extent in the literature.No funding source. 22 experiments were conducted with in-kind support (employee time and company access) from Beckhoff Automation, Herman Miller and fluiconnecto as well as University of Cambridge students (see Table 1)