“…Case studies and practical implementation: These strategies play an important role in AR methodology-for example, Na'amnh et al [107] and Wang et al [85] developed and tested AR systems in real industrial situations, such as mechanical assembly and specific manufacturing processes. This methodology is iterative and reflective, adapting the AR design to the specific needs of the work environment.…”
Augmented reality (AR) technology is making a strong appearance on the industrial landscape, driven by significant advances in technological tools and developments. Its application in areas such as training and assistance has attracted the attention of the research community, which sees AR as an opportunity to provide operators with a more visual, immersive and interactive environment. This article deals with an analysis of the integration of AR in the context of the fourth industrial revolution, commonly referred to as Industry 4.0. Starting with a systematic review, 60 relevant studies were identified from the Scopus and Web of Science databases. These findings were used to build bibliometric networks, providing a broad perspective on AR applications in training and assistance in the context of Industry 4.0. The article presents the current landscape, existing challenges and future directions of AR research applied to industrial training and assistance based on a systematic literature review and citation network analysis. The findings highlight a growing trend in AR research, with a particular focus on addressing and overcoming the challenges associated with its implementation in complex industrial environments.
“…Case studies and practical implementation: These strategies play an important role in AR methodology-for example, Na'amnh et al [107] and Wang et al [85] developed and tested AR systems in real industrial situations, such as mechanical assembly and specific manufacturing processes. This methodology is iterative and reflective, adapting the AR design to the specific needs of the work environment.…”
Augmented reality (AR) technology is making a strong appearance on the industrial landscape, driven by significant advances in technological tools and developments. Its application in areas such as training and assistance has attracted the attention of the research community, which sees AR as an opportunity to provide operators with a more visual, immersive and interactive environment. This article deals with an analysis of the integration of AR in the context of the fourth industrial revolution, commonly referred to as Industry 4.0. Starting with a systematic review, 60 relevant studies were identified from the Scopus and Web of Science databases. These findings were used to build bibliometric networks, providing a broad perspective on AR applications in training and assistance in the context of Industry 4.0. The article presents the current landscape, existing challenges and future directions of AR research applied to industrial training and assistance based on a systematic literature review and citation network analysis. The findings highlight a growing trend in AR research, with a particular focus on addressing and overcoming the challenges associated with its implementation in complex industrial environments.
“…Malta et al [67] introduced an AR maintenance assistant utilising YOLOv5, while Fiorentino et al [42] employed interactive projections for maintenance tasks. Na'amnh et al [70] developed an AR application to simplify the mechanical bar-bending process, and Liu et al [81] proposed an AR-based intelligent predictive maintenance approach for industrial machinery integrated with IoT.…”
In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies. This article focuses on exploring the integration of AR in Industry 4.0, with a particular emphasis on its role in improving technical assistance and training. The research addresses the ways in which AR not only facilitates more efficient processes but also acts as an essential bridge for training and skills development in constantly changing technological environments. It investigates the significant impact of AR on both optimising work processes and training workers to meet the emerging challenges of Industry 4.0. Through a qualitative analysis, the studies are categorised according to their application domains, grouping them into specific thematic areas. Subsequently, a meta-analysis is conducted to determine the actual impact of AR in the sector. The findings reveal a positive and significant correlation between the implementation of AR and its effectiveness in assistance and training in the framework of Industry 4.0. Finally, the article delves into an analysis of current limitations and challenges, providing insights into possible developments and trends in the use of AR for assistance and training in Industry 4.0.
“…Implementation of augmented reality to train unskilled operators on a busbar bending process resulted in easier achievement of the task [32]. General Electric (GE) achieved an increase in productivity and efficiency by applying AR [33].…”
Section: Examples From the Literaturementioning
confidence: 99%
“…General Electric (GE) achieved an increase in productivity and efficiency by applying AR [33]. Honeywell also improved its operator training by implementing AR [32]. DHL's need for traditional instructors is reduced while the onboarding speed for new employees is increased by providing AR real-time training [28].…”
Training within Industry was created under World War II by the U.S. Department of War, within the War Manpower Commission, to assist defense industries meet the high production output demand from less-or inexperienced labor. It ran from 1940 to 1945, made its way to Japan after the war and became a foundational component of the Toyota Production System (TPS). TWI is a well-proven lean education methodology consists of four main modules: Job Instructions (JI), Job Relations (JR), Job Methods (JM) and Program Development. This paper aims to explore combining TWI Job Instructions (JI) module with extended reality (XR) smart glasses and technologies that may create an effective and innovative lean education program.
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