Wu, Mingyu and Koh, Ye Sheng and Yeong, Che Fai and Goh, Kai Woon and Marvin Dares, Marvin Dares and Lee, Eileen Su Ming and Holderbaum, William and Sunar, Mohd. Shahrizal (2024) Optimizing assembly processes with augmented reality: a case study on TurtleBots. Indonesian Journal of Electrical Engineering and Computer ScienceOpen Access, 35 (3). pp. 1547-1555. ISSN 2502-4752
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Official URL: http://dx.doi.org/10.11591/ijeecs.v35.i3.pp1547-15...
Abstract
Augmented reality (AR) technology is revolutionizing traditional assembly processes, offering intuitive and interactive guidance that significantly enhances operational efficiency and accuracy. This study investigates the impact of AR on the assembly of Turtlebots, a complex task representative of industrial applications. Through a comparative analysis involving traditional paper manuals, modified paper manuals, and AR-based manuals, the benefits of AR integration are quantitatively assessed. Participants utilizing AR-based manuals completed the Turtlebot assembly 21.72% faster than those using traditional paper manuals, with a notable reduction in assembly time from an average of 03:00:40 to 02:21:26. Furthermore, the incidence of assembly errors significantly decreased, with AR manual users making an average of 2.25 errors compared to 5 by paper manual users. These findings underscore the potential of AR to expedite complex assembly tasks and enhance the accuracy of these processes. The study highlights the novel application of AR in improving both the speed and quality of assembly in an industrial context, demonstrating AR's role as a pivotal technology for the future of manufacturing.
Item Type: | Article |
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Uncontrolled Keywords: | Assembly; Augmented reality; Industrial application; Mobile robot; Operational efficiency; TurtleBot. |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 108984 |
Deposited By: | Muhamad Idham Sulong |
Deposited On: | 27 Jan 2025 01:09 |
Last Modified: | 27 Jan 2025 01:09 |
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