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Cited by 446

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard

Open access
Fraga-Lamas, Paula, Fernandez-Carames, Tiago M., Blanco-Novoa, Oscar, Vilar-Montesinos, Miguel A.·2018·IEEE Access

Abstract

Shipbuilding companies are upgrading their inner workings in order to create Shipyards 4.0, where the principles of Industry 4.0 are paving the way to further digitalized and optimized processes in an integrated network. Among the different Industry 4.0 technologies, this paper focuses on augmented reality, whose application in the industrial field has led to the concept of industrial augmented reality (IAR). This paper first describes the basics of IAR and then carries out a thorough analysis of the latest IAR systems for industrial and shipbuilding applications. Then, in order to build a practical IAR system for shipyard workers, the main hardware and software solutions are compared. Finally, as a conclusion after reviewing all the aspects related to IAR for shipbuilding, it proposed an IAR system architecture that combines cloudlets and fog computing, which reduce latency response and accelerate rendering tasks while offloading compute intensive tasks from the cloud.

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Metadata

Authors
Fraga-Lamas, P., Fernandez-Carames, T. M., Blanco-Novoa, O., & Vilar-Montesinos, M. A.
Venue
IEEE Access
Published
2018
Volume
6
Pages
13358-13375
ISSN
2169-3536 (ISSN-L)
OpenAlex
W2791480559
Cited by
446
References
11
FWCI
28.41
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard. https://app.cochat.ai/papers/10.1109/access.2018.2808326
The paper
Fraga-Lamas, P., Fernandez-Carames, T. M., Blanco-Novoa, O., & Vilar-Montesinos, M. A. (2018). A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard. IEEE Access. https://doi.org/10.1109/access.2018.2808326

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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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