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Simon, J.; Gogolák, L.; Sárosi, J.; Fürstner, I. Augmented Reality Based Distant Maintenance Approach. Encyclopedia. Available online: https://encyclopedia.pub/entry/47596 (accessed on 16 May 2024).
Simon J, Gogolák L, Sárosi J, Fürstner I. Augmented Reality Based Distant Maintenance Approach. Encyclopedia. Available at: https://encyclopedia.pub/entry/47596. Accessed May 16, 2024.
Simon, János, László Gogolák, József Sárosi, Igor Fürstner. "Augmented Reality Based Distant Maintenance Approach" Encyclopedia, https://encyclopedia.pub/entry/47596 (accessed May 16, 2024).
Simon, J., Gogolák, L., Sárosi, J., & Fürstner, I. (2023, August 03). Augmented Reality Based Distant Maintenance Approach. In Encyclopedia. https://encyclopedia.pub/entry/47596
Simon, János, et al. "Augmented Reality Based Distant Maintenance Approach." Encyclopedia. Web. 03 August, 2023.
Augmented Reality Based Distant Maintenance Approach
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Augmented Reality (AR) is a technology that overlays virtual objects onto the real world, enabling operators to visualize and interact with virtual objects in real-time.

augmented reality distant maintenance Industry 4.0 telepresence

1. Introduction

Industry 4.0 has revolutionized the manufacturing industry by integrating advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and Augmented Reality (AR) into production and maintenance processes. One of the significant applications of Industry 4.0 in maintenance is the use of AR to enhance the maintenance approach. AR is a technology that overlays virtual objects onto the real world, enabling operators to visualize and interact with virtual objects in real-time [1] (see Figure 1). The benefits of an AR-based maintenance system are numerous. First, it reduces the time required to perform maintenance tasks, which improves equipment availability and reduces downtime. Second, it improves the quality of maintenance work by providing real-time instructions and reducing human errors. Third, it reduces the risk of accidents by providing remote assistance to maintenance personnel in hazardous environments. Fourth, it improves the training of maintenance personnel by providing a hands-on, immersive experience.
Figure 1. General AR concept.
The implementation of an AR-based maintenance system requires a step-by-step approach. The first step is to identify the maintenance processes that can benefit from AR technology [2]. This includes processes that involve complex equipment, hazardous environments, or where remote assistance is needed. The second step is to select appropriate AR devices and software that meet the requirements of the maintenance processes identified in the first step. The third step is to develop AR applications that are customized to the maintenance processes and equipment (see Figure 2). This includes developing 3D models of the equipment and creating virtual overlays that provide instructions and guidance to maintenance personnel.
Figure 2. General Unity/Vuforia framework [3].

2. Augmented Reality Based Distant Maintenance Approach

In [1], the main maintenance areas supported and enabled by Industry 4.0 technologies were discussed, along with the introduction of an Industry 4.0-based predictive maintenance approach for the manufacturing industry. In [2], various Industry 4.0 enabling technologies that enhance operational flexibility in final assembly were presented, with proven examples of their application in increasing flexibility. In [3], the researchers proposed an Augmented Reality (AR)-based system that integrates the existing Manufacturing Execution Systems (MES) with Cyber-Physical Systems (CPS), creating a Cognition Level. The study highlights the opportunities offered by AR technologies to CPS through an application scenario analyzed in a real factory setting. The authors in [4] presented results from six case studies involving over two hundred respondents from academia and the industry, focusing on the usage and strategies for implementing different xR technologies. Paper [5] focused on the user experience (UX) of AR-based instructions for assembly. An evaluation matrix and an AR prototype were developed and assessed in a UX test, collecting data on both the hedonic and pragmatic qualities. In [6], the authors conducted a systematic literature review (SLR) to analyze I4.0 research studies in the automotive sector. The objective of [7] was to propose an original framework that investigates the impact of the Industry 4.0 principles on assembly system design, describing the traditional dimensions of this problem and the evolution of the industrial environment over the last three centuries. In [8], the authors provided a brief survey of current use cases in factory applications and industrial inspections that are actively being developed. In [9], an efficient AR system was proposed, which enables the locating of a component in the manufacturing plant and the visualization of maintenance instructions for the corresponding failure modes in a handheld and vivid manner on the operators’ mobile device. The activity within the industrial plant is recorded by a camera, which serves as the sensory input for the proposed AR system. The authors in [10] constructed a platform by integrating AR goggles, enabling the acquisition of data for the technical evaluation of rotary components and facilitating direct interaction with the user. The platform presented allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system in order to determine the technical condition of a wind turbine model. The image processing system, which measures frequencies generated by the machine, is used for monitoring purposes. A new system architecture was presented in [11] for controlling industrial devices using Mixed Reality (MR) applications. Additionally, a new method for measuring the distance between real and virtual points is proposed based on this system’s architecture. The research involves the use of a physical robot and its Digital Twin (DT). The paper demonstrates the feasibility of controlling the robot and its DT using gestures recognized by Mixed Reality goggles. The aim of [12] was to demonstrate the current state-of-the-art of AR in maintenance and highlight the most relevant technical limitations, as revealed by the results of a systematic literature review. The analysis involved filtering a large number of publications and identifying 30 primary studies published between 1997 and 2017. The findings indicated a high level of fragmentation among hardware, software, and AR solutions, resulting in complexity when selecting and developing AR systems. The study’s results shed light on areas where AR technology is still lacking maturity. The user, technical, environmental, and regulative requirements for an AR maintenance worker support system were presented in [13], based on the analysis of three diverse production sites.

3. The Role of AR in Industry 4.0 Maintenance Procedures

In the context of Industry 4.0, Augmented Reality (AR) has emerged as a transformative technology, revolutionizing maintenance procedures and enhancing the overall efficiency and effectiveness. AR plays a crucial role in empowering maintenance personnel by providing them with real-time information, intuitive guidance, and improved situational awareness. One of the key contributions of AR in Industry 4.0 maintenance procedures is the ability to overlay digital information onto the physical environment. By wearing AR-enabled devices such as smart glasses or using AR applications on mobile devices, maintenance technicians can access critical data, instructions, and visualizations directly in their field of view. This capability enables technicians to quickly identify and diagnose issues, locate components, and perform repairs or maintenance tasks more effectively. According to [14], AR also facilitates remote collaboration and knowledge sharing among maintenance teams. With AR, experts can provide remote assistance to technicians in real time, regardless of their physical location. Through AR-enabled communication platforms, technicians can share live video feeds, annotations, and 3D models, allowing experts to guide them through complex maintenance procedures. This collaborative approach not only improves the accuracy and speed of maintenance activities but also reduces the downtime and the need for on-site visits. AR technology finds extensive applications across various domains within the digital factory, enabling operators to remain updated on crucial events and engage in collaborative tasks with digital assets. In maintenance procedures, for instance, operators utilize their mobile devices to assign and track their tasks throughout the day, interact with production equipment, and access digitized step-by-step procedures via AR frameworks. Furthermore, the integration of artificial intelligence technologies facilitates mechanical intelligence, which plays a significant role in fostering collaboration between humans and machines. This aspect proves particularly valuable in modern manufacturing environments, as machines, despite their limited understanding and management of the surrounding environment, can still contribute effectively.

References

  1. García, J.R.R.; Martinetti, A.; Becker, J.M.J.; Singh, S.; van Dongen, L.A. Towards an industry 4.0-based maintenance approach in the manufacturing processes. In Research Anthology on Cross-Industry Challenges of Industry 4.0; IGI Global: Hershey, PA, USA, 2021; pp. 1219–1243.
  2. Salunkhe, O.; Fast-Berglund, Å. Increasing operational flexibility using Industry 4.0 enabling technologies in final assembly. In Proceedings of the 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Cardiff, UK, 15–17 June 2020.
  3. Di Pace, A.; Fenza, G.; Gallo, M.; Loia, V.; Meglio, A.; Orciuoli, F. Implementing the Cognition Level for Industry 4.0 by integrating Augmented Reality and Manufacturing Execution Systems. In Proceedings of the 34th International Conference on Advanced Information Networking and Applications (AINA-2020), Caserta, Italy, 28 March 2020.
  4. Fast-Berglund, Å.; Gong, L.; Li, D. Testing and validating Extended Reality (xR) technologies in manufacturing. Procedia Manuf. 2018, 25, 31–38.
  5. Alenljung, Z.; Lindblom, J. User experience in augmented reality: A holistic evaluation of a prototype for assembly instructions. In Proceedings of the Design, User Experience, and Usability: Design for Contemporary Technological Environments: 10th International Conference, Virtual Event, 24–29 July 2021.
  6. Wankhede, V.A.; Vinodh, S. State of the art review on Industry 4.0 in manufacturing with the focus on automotive sector. Int. J. Lean Six Sigma 2022, 13, 692–732.
  7. Bortolini, M.; Ferrari, E.; Gamberi, M.; Pilati, F.; Faccio, M. Assembly system design in the Industry 4.0 era: A general framework. Ifac-Pap. 2017, 50, 5700–5705.
  8. Makhataeva, Z.; Varol, H.A. Augmented Reality for Robotics: A Review. Robotics 2020, 9, 21.
  9. Konstantinidis, F.K.; Kansizoglou, I.; Santavas, N.; Mouroutsos, S.G.; Gasteratos, A. MARMA: A Mobile Augmented Reality Maintenance Assistant for Fast-Track Repair Procedures in the Context of Industry 4.0. Machines 2020, 8, 88.
  10. Lalik, K.; Wątorek, F. Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles. Energies 2021, 14, 7632.
  11. Lalik, K.; Flaga, S. A Real-Time Distance Measurement System for a Digital Twin Using Mixed Reality Goggles. Sensors 2021, 21, 7870.
  12. Palmarini, R.; ErkoyuncuJ, A.; Rajkumar, R.; Torabmostaedi, H. A systematic review of augmented reality applications in maintenance. Robot. Comput. Integr. Manuf. 2018, 49, 215–228.
  13. Lorenz, M.; Knopp, S.; Klimant, P. Industrial Augmented Reality: Requirements for an Augmented Reality Maintenance Worker Support System. In Proceedings of the 2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), Munich, Germany, 16–20 October 2018.
  14. Konstantinidis, F.K.; Myrillas, N.; Mouroutsos, S.G.; Koulouriotis, D.; Gasteratos, A. Assessment of Industry 4.0 for Modern Manufacturing Ecosystem: A Systematic Survey of Surveys. Machines 2022, 10, 746.
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