Real-Time Remote Maintenance Support Based on Augmented Reality (AR)
Source abstract
Abstract
In the realm of the current industrial revolution, interesting innovations as well as new techniques are constantly being introduced by offering fertile ground for further investigation and improvement in the industrial engineering domain. More specifically, cutting-edge digital technologies in the field of Extended Reality (XR) have become mainstream including Augmented Reality (AR). Furthermore, Cloud Computing has enabled the provision of high-quality services, especially in the controversial field of maintenance. However, since modern machines are becoming more complex, maintenance must be carried out from experienced and well-trained personnel, while overseas support is timely and financially costly. Although AR is a back-bone technology facilitating the development of robust maintenance support tools, they are limited to the provision of predefined scenarios, covering only a limited number of scenarios. This research work aims to address this emerging challenge with the design and development of a framework, for the support of remote maintenance and repair operation based on AR, by creating suitable communication channels between the shop-floor technicians and the expert engineers who are utilizing real-time feedback from the operator’s field of view. The applicability of the developed framework is tested in vitro in a lab-based machine shop and in a real-life industrial scenario.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Augmented Reality Applications · Digital Transformation in Industry · IoT and Edge/Fog Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece
References (37)
Show source-provided references
1. Mourtzis, D., Vlachou, E., Milas, N., and Xanthopoulos, N. (2015, January 24–26). A Cloud-based Approach for Maintenance of Machine Tools and Equipment Based on Shop-floor Monitoring. Proceedings of the 48th CIRP Conference on Manufacturing Systems, Ischia, Italy.
2. (2020, January 02). Predictive Maintenance: Taking Pro-Active Measures Based on Advanced Data Analytics to Predict and Avoid Machine Failure. Available online: https://www2.deloitte.com/content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf.
3. Remote machine maintenance system through Internet and mobile communication10.1007/s00170-005-0236-1 ↗
4. Wang, J., Feng, Y., Zeng, C., and Li, S. (2014, January 18–22). An augmented reality based system for remote collaborative maintenance instruction of complex products. Proceedings of the 2014 IEEE International Conference on Automation Science and Engineering (CASE), Taipei, Taiwan.10.1109/CoASE.2014.6899343 ↗
5. Supporting remote maintenance in industry 4.0 through augmented reality10.1016/j.promfg.2017.07.257 ↗
6. A novel maintenance system for equipment serviceability improvement10.1016/j.cirp.2013.03.091 ↗
7. Cloud-based augmented reality remote maintenance through shop-floor monitoring: A product-service system approach10.1115/1.4035721 ↗
8. Mourtzis, D., Zogopoulos, V., Katagis, I., and Lagios, P. (2018, January 23–25). Augmented Reality based Visualization of CAM Instructions towards Industry 4.0 paradigm: A CNC Bending Machine case study. Proceedings of the 28th CIRP Design Conference 2018, Nantes, France.10.1016/j.procir.2018.02.045 ↗
9. A Survey of Industrial Augmented Reality10.1016/j.cie.2019.106159 ↗
10. A systematic review of augmented reality applications in maintenance10.1016/j.rcim.2017.06.002 ↗
11. A systematic review of Augmented Reality content-related techniques for knowledge transfer in maintenance applications10.1016/j.compind.2018.08.007 ↗
12. Berglund, F.Å., Gong, L., and Li, D. (2018, January 16–18). Testing and validating Extended Reality (xR) technologies in manufacturing. Proceedings of the 8th Swedish Production Symposium (SPS 2018), Stokholm, Sweeden.
13. (2020, February 16). What Is Extended Reality Technology? A Simple Explanation for Anyone. Available online: https://www.forbes.com/sites/bernardmarr/2019/08/12/what-is-extended-reality-technology-a-simple-explanation-for-anyone/#69b6421f7249.
14. Mourtzis, D. (2019). Simulation in the design and operation of manufacturing systems: State of the art and new trends. Int. J. Prod. Res., 1–23.
15. (2020, January 02). 4 Types of Maintenance Strategy, Which one to Choose?. Available online: https://new.abb.com/medium-voltage/service/maintenance/feature-articles/4-types-of-maintenance-strategy-which-one-to-choose.
16. Mourtzis, D., and Doukas, M. (2014, January 7–9). Design and Planning of Manufacturing Networks for Mass Customisation and Personalisation: Challenges and Outlook. Proceedings of the 2nd CIRP Robust Manufacturing Conference (RoMac 2014), Bremen, Germany.
17. From cloud computing to cloud manufacturing10.1016/j.rcim.2011.07.002 ↗
18. A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance10.1016/j.jmsy.2018.05.008 ↗
19. A Survey of Augmented Reality10.1162/pres.1997.6.4.355 ↗
20. The Most Important Challenge Facing Augmenting reality10.1162/PRES_a_00264 ↗
21. Mourtzis, D., Zogopoulos, B., and Vlachou, E. (2017, January 3–5). Augmented Reality Application to Support Remote Maintenance as a Service in the Robotics Industry. Proceedings of the 50th CIRP conference on Manufacturing Systems, Taichung City, Taiwan.10.1016/j.procir.2017.03.154 ↗
22. Exploring the Benefits of Augmented Reality Documentation for Maintenance and Repair10.1109/TVCG.2010.245 ↗
23. Mourtzis, D., Angelopoulos, J., and Boli, N. (2018, January 11–13). Maintenance assistance application of Engineering to Order manufacturing equipment: A Product Service System (PSS) approach. Proceedings of the 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018, Bergamo, Italy.10.1016/j.ifacol.2018.08.263 ↗
24. Mourtzis, D., Xanthi, F., and Zogopoulos, V. (2019, January 12–14). An Adaptive Framework for Augmented Reality Instructions Considering Workforce Skill. Proceedings of the 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia.10.1016/j.procir.2019.03.063 ↗
25. A practical augmented reality-assisted maintenance system framework for adaptive user support10.1016/j.rcim.2019.03.010 ↗
26. Chryssolouris, G. (2006). Manufacturing Systems: Theory and Practice, Springer. [2nd ed.].
27. Chen, J., Gusikhin, O., Finkenstaedt, W., and Liu, Y. (2019, January 28–30). Maintenance, Repair, and Operations Parts Inventory Management in the Era of Industry 4.0. Proceedings of the 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019, Berlin, Germany.10.1016/j.ifacol.2019.11.171 ↗
28. Bokrantz, J., Skoogh, A., Berlin, C., Wuest, T., and Stahre, J. (2019). Smart Maintenance: An empirically grounded conceptualization. Int. J. Prod. Econ., 107534.10.1016/j.ijpe.2019.107534 ↗
29. Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case10.1016/j.jmsy.2019.11.004 ↗
30. A predictive model for the maintenance of industrial machinery in the context of industry 4.010.1016/j.engappai.2019.103289 ↗
31. Decision Making in Predictive Maintenance: Literature Review and Research Agenda for Industry 4.010.1016/j.ifacol.2019.11.226 ↗
32. On a Predictive Maintenance Platform for Production Systems10.1016/j.procir.2012.07.039 ↗
33. On a versatile scheduling concept of maintenance activities for increased availability of production resources10.1016/j.procir.2018.09.065 ↗
34. (2020, February 26). Agora.io. Available online: https://www.agora.io/en/.
35. (2020, February 26). GIGA Video Streamer. Available online: https://assetstore.unity.com/packages/tools/video/giga-video-streamer-125456?_ga=2.75845011.740357347.1582886552-1421986738.1578039987.
36. (2020, February 26). Microsoft HoloLens Specification. Available online: https://www.windowscentral.com/hololens-hardware-specs.
37. Bengtsson, M., and Kurdve, M. (2016, January 22–24). Machining Equipment Life Cycle Costing Model with Dynamic Maintenance Cost. Proceedings of the 23rd CIRP Conference on Life Cycle Engineering, Berlin, Germany.10.1016/j.procir.2016.03.110 ↗