The DOI matches its Crossref record; 115 of the 115 references it cites were found in a registry or an index.
Augmented reality in support of intelligent manufacturing – A systematic literature review
Open accessAbstract
Abstract Industry increasingly moves towards digitally enabled ‘smart factories’ that utilise the internet of things (IoT) to realise intelligent manufacturing concepts like predictive maintenance or extensive machine to machine communication. A core technology to facilitate human integration in such a system is augmented reality (AR), which provides people with an interface to interact with the digital world of a smart factory. While AR is not ready yet for industrial deployment in some areas, it is already used in others. To provide an overview of research activities concerning AR in certain shop floor operations, a total of 96 relevant papers from 2011 to 2018 are reviewed. This paper presents the state of the art, the current challenges, and future directions of manufacturing related AR research through a systematic literature review and a citation network analysis. The results of this review indicate that the context of research concerning AR gets increasingly broader, especially by addressing challenges when implementing AR solutions.
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Cites
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Cited by
Ghobakhloo, M., Iranmanesh, M., Grybauskas, A., Vilkas, M., & Petraitė, M. (2021) · Business Strategy and the Environment · doi:10.1002/bse.2867 · Cited by 462
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
Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2020) · Frontiers in Mechanical Engineering · doi:10.3389/fmech.2020.578379 · Cited by 70
Madhankumar, S., Prawin Sankar, T. A., Shibin Thomas, S., Brundhavani, G., Paul, P., & Girishkumar, V. (2021) · IOP Conference Series: Materials Science and Engineering · doi:10.1088/1757-899x/1059/1/012016 · Cited by 7
Metadata
- Authors
- Egger, J., & Masood, T.
- Venue
- Computers & Industrial Engineering
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 140
- Pages
- 106195
- ISSN
- 0360-8352 (ISSN-L)
- OpenAlex
- W2992509920
- Cited by
- 391
- References
- 115
- FWCI
- 7.95
- Type
- journal article
- Language
- en
- Open access
- green
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
