The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Smart augmented reality instructional system for mechanical assembly towards worker-centered intelligent manufacturing
Open accessAbstract
Quality and efficiency are crucial indicators of any manufacturing company. Many companies are suffering from a shortage of experienced workers across the production line to perform complex assembly tasks. To reduce time and error in an assembly task, a worker-centered system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The integrated AR is designed to provide on-site instructions including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is trained on a synthetic tool dataset. The dataset is generated using CAD models of tools and displayed onto a 2D scene without using real tool images. By experimenting the system to a mechanical assembly of a CNC carving machine, the result of a designed experiment shows that the system helps reduce the time and errors of the given assembly tasks by 33.2 % and 32.4 %, respectively. With the integrated system, an efficient, customizable smart AR instruction system capable of sensing, characterizing requirements, and enhancing worker’s performance has been built and demonstrated.
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Cited by
Jamwal, A., Agrawal, R., Sharma, M., & Giallanza, A. (2021) · Applied Sciences · doi:10.3390/app11125725 · Cited by 458
Xia, K., Sacco, C., Kirkpatrick, M., Saidy, C., Nguyen, L., Kircaliali, A., & Harik, R. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.012 · Cited by 406
An Overview of Augmented Reality
Arena, F., Collotta, M., Pau, G., & Termine, F. (2022) · Computers · doi:10.3390/computers11020028 · Cited by 389
Eswaran, M., & Bahubalendruni, M. V. A. R. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.09.016 · Cited by 308
Real-Time Identification of Look-Alike Medical Vials Using Mixed Reality-Enabled Deep Learning
Mahmud, B. U., Hong, G., Lalwani, V. R., Brown, N., & Asher, Z. D. (2025) · Future Internet · doi:10.3390/fi17050223 · Cited by 8
Metadata
- Authors
- Lai, Z.-H., Tao, W., Leu, M. C., & Yin, Z.
- Venue
- Journal of Manufacturing Systems
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 55
- Pages
- 69-81
- ISSN
- 0278-6125 (ISSN-L)
- OpenAlex
- W3011453732
- Cited by
- 214
- References
- 9
- FWCI
- 10.81
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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