Augmented reality remote maintenance system based on fog computing and 5G networks

In recent years, industry-related research has proposed to improve personnel efficiency using augmented reality (AR). However, with the increasing complexity of the production line in the industrial field, the problem of insufficient computing performance of AR hardware for applications arises. Therefore, this study deployed the image processing operation of the AR system to the fog nodes and used the 5G network to ensure the image transmission delay between AR devices and fog nodes to resolve the problem of insufficient AR hardware performance and improve the scalability of the AR system. On this basis, the AR monitoring and remote maintenance system is developed. The fog node is used as the relay station to integrate data from CNC-machines and remote maintenance platforms into the AR system. Field personnel can monitor the CNC status and receive remote expert maintenance instructions through AR devices and can immediately detect and resolve CNC anomalies to reduce the additional cost caused by temporary shutdown. In this study, 5G is used for image transmission to ensure that the delay is less than 20 ms. Compared with local image processing on AR devices, the performance is improved by 28%. On this basis, the monitoring system is developed to update AR visualization data with a frequency of 209 ms. This system is used for maintenance assistance. The test results indicate that 30% maintenance efficiency improvement is achieved for users unfamiliar with CNC maintenance tasks. The aforementioned results prove the efficiency and feasibility of the AR remote maintenance system architecture in the industrial field and provide a solution for the AR application in the industrial field.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Published
2026-06-25
DOI
https://doi.org/10.1177/09544054261458706
Primary Topic
Digital Transformation in Industry
Type
article
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article

Augmented reality remote maintenance system based on fog computing and 5G networks

Shang-Liang Chen, Hong-Yuan Yang
Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
Digital Transformation in Industry
article

Augmented reality remote maintenance system based on fog computing and 5G networks

Shang-Liang Chen, Hong-Yuan Yang
article en

Abstract

In recent years, industry-related research has proposed to improve personnel efficiency using augmented reality (AR). However, with the increasing complexity of the production line in the industrial field, the problem of insufficient computing performance of AR hardware for applications arises. Therefore, this study deployed the image processing operation of the AR system to the fog nodes and used the 5G network to ensure the image transmission delay between AR devices and fog nodes to resolve the problem of insufficient AR hardware performance and improve the scalability of the AR system. On this basis, the AR monitoring and remote maintenance system is developed. The fog node is used as the relay station to integrate data from CNC-machines and remote maintenance platforms into the AR system. Field personnel can monitor the CNC status and receive remote expert maintenance instructions through AR devices and can immediately detect and resolve CNC anomalies to reduce the additional cost caused by temporary shutdown. In this study, 5G is used for image transmission to ensure that the delay is less than 20 ms. Compared with local image processing on AR devices, the performance is improved by 28%. On this basis, the monitoring system is developed to update AR visualization data with a frequency of 209 ms. This system is used for maintenance assistance. The test results indicate that 30% maintenance efficiency improvement is achieved for users unfamiliar with CNC maintenance tasks. The aforementioned results prove the efficiency and feasibility of the AR remote maintenance system architecture in the industrial field and provide a solution for the AR application in the industrial field.

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture
National Cheng Kung University (TW)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Digital Transformation in Industry
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