Validating the Use of Smart Glasses in Industrial Quality Control: A Case Study
| Autor: | José Silva, Pedro Coelho, Luzia Saraiva, Paulo Vaz, Pedro Martins, Alfonso López-Rivero |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Applied Sciences, Vol 14, Iss 5, p 1850 (2024) |
| Druh dokumentu: | article |
| ISSN: | 14051850 2076-3417 |
| DOI: | 10.3390/app14051850 |
| Popis: | Effective quality control is crucial in industrial manufacturing for influencing efficiency, product dependability, and customer contentment. In the constantly changing landscape of industrial production, conventional inspection methods may fall short, prompting the need for inventive approaches to enhance precision and productivity. In this study, we investigate the application of smart glasses for real-time quality inspection during assembly processes. Our key innovation involves combining smart glasses’ video feed with a server-based image recognition system, utilizing the advanced YOLOv8 model for accurate object detection. This integration seamlessly merges mixed reality (MR) with cutting-edge computer vision algorithms, offering immediate visual feedback and significantly enhancing defect detection in terms of both speed and accuracy. Carried out in a controlled environment, our research provides a thorough evaluation of the system’s functionality and identifies potential improvements. The findings highlight that MR significantly elevates the efficiency and reliability of traditional inspection methods. The synergy of MR and computer vision opens doors for future advancements in industrial quality control, paving the way for more streamlined and dependable manufacturing ecosystems. |
| Databáze: | Directory of Open Access Journals |
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