User Experience Evaluation of AR Assisted Industrial Maintenance and Support Applications
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866916507483635712 |
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| author | Nagy, Akos Spyridis, Yannis Mills, Gregory J Argyriou, Vasileios |
| author_facet | Nagy, Akos Spyridis, Yannis Mills, Gregory J Argyriou, Vasileios |
| contents | The paper introduces an innovative approach to industrial maintenance leveraging augmented reality (AR) technology, focusing on enhancing the user experience and efficiency. The shift from traditional to proactive maintenance strategies underscores the significance of maintenance in industrial systems. The proposed solution integrates AR interfaces, particularly through Head-Mounted Display (HMD) devices, to provide expert personnel-aided decision support for maintenance technicians, with the association of Artificial Intelligence (AI) solutions. The study explores the user experience aspect of AR interfaces in a simulated industrial environment, aiming to improve the maintenance processes' intuitiveness and effectiveness. Evaluation metrics such as the NASA Task Load Index (NASA-TLX) and the System Usability Scale (SUS) are employed to assess the usability, performance, and workload implications of the AR maintenance system. Additionally, the paper discusses the technical implementation, methodology, and results of experiments conducted to evaluate the effectiveness of the proposed solution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_17348 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | User Experience Evaluation of AR Assisted Industrial Maintenance and Support Applications Nagy, Akos Spyridis, Yannis Mills, Gregory J Argyriou, Vasileios Human-Computer Interaction Systems and Control The paper introduces an innovative approach to industrial maintenance leveraging augmented reality (AR) technology, focusing on enhancing the user experience and efficiency. The shift from traditional to proactive maintenance strategies underscores the significance of maintenance in industrial systems. The proposed solution integrates AR interfaces, particularly through Head-Mounted Display (HMD) devices, to provide expert personnel-aided decision support for maintenance technicians, with the association of Artificial Intelligence (AI) solutions. The study explores the user experience aspect of AR interfaces in a simulated industrial environment, aiming to improve the maintenance processes' intuitiveness and effectiveness. Evaluation metrics such as the NASA Task Load Index (NASA-TLX) and the System Usability Scale (SUS) are employed to assess the usability, performance, and workload implications of the AR maintenance system. Additionally, the paper discusses the technical implementation, methodology, and results of experiments conducted to evaluate the effectiveness of the proposed solution. |
| title | User Experience Evaluation of AR Assisted Industrial Maintenance and Support Applications |
| topic | Human-Computer Interaction Systems and Control |
| url | https://arxiv.org/abs/2410.17348 |