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Digital Twin and 3D Web-based Use Cases in Industry

Published: 02 November 2022 Publication History

Abstract

Multi-physical modeling combined with data-driven decision making is giving rise to a new paradigm, the "digital twin." The digital twin is a living digital model of a system or physical asset that continuously adapts to operational changes based on real-time data. When properly designed, a digital twin can help predict the future behavior of its corresponding physical counterpart. This paper presents a series of use cases that illustrate the role of a digital twin in different stages of the industrial product lifecycle. The use cases are implemented using 3D web technology for user interfaces and web standards (X3D and glTF) for data exchange between modules. The contribution of this work consists of a set of lessons learnt and some hints on future synergies between digital twin and 3D web technologies.

References

[1]
Nerea Aranjuelo, Sara García, Estíbaliz Loyo, Luis Unzueta, and Oihana Otaegui. 2021. Key strategies for synthetic data generation for training intelligent systems based on people detection from omnidirectional cameras. Computers & Electrical Engineering 92 (2021), 107105.
[2]
Ruth N Bolton, Janet R McColl-Kennedy, Lilliemay Cheung, Andrew Gallan, Chiara Orsingher, Lars Witell, and Mohamed Zaki. 2018. Customer experience challenges: bringing together digital, physical and social realms. Journal of Service Management 29, 5 (2018), 776–808.
[3]
María del Puy Carretero, Sara García, Aitor Moreno, Nieves Alcain, and Idurre Elorza. 2021. Methodology to create virtual reality assisted training courses within the Industry 4.0 vision. Multimedia Tools and Applications 80, 19 (2021), 29699–29717.
[4]
Mohan Baruwal Chhetri, Shonali Krishnaswamy, and Seng Wai Loke. 2004. Smart virtual counterparts for learning communities. In International Conference on Web Information Systems Engineering. Springer, 125–134.
[5]
Abdulmotaleb El Saddik. 2018. Digital twins: The convergence of multimedia technologies. IEEE multimedia 25, 2 (2018), 87–92.
[6]
Ander García, Ander Arbelaiz, Javier Franco, Xabier Oregui, Bruno Simões, Zelmar Etxegoien, and Andoni Bilbao. 2019. Technologies for Industry 4.0 Data Solutions. In Technological Developments in Industry 4.0 for Business Applications. IGI Global, 71–99.
[7]
Michael Grieves. 2014. Digital twin: manufacturing excellence through virtual factory replication. White paper 1, 2014 (2014), 1–7.
[8]
Daniel Mejia, Jairo R Sánchez, Álvaro Segura, Oscar Ruiz-Salguero, Jorge Posada, and Carlos Cadavid. 2017. Mesh segmentation and texture mapping for dimensional inspection in web3d. In Proceedings of the 22nd International Conference on 3D Web Technology. 1–4.
[9]
Elisa Negri, Luca Fumagalli, and Marco Macchi. 2017. A review of the roles of digital twin in CPS-based production systems. Procedia manufacturing 11 (2017), 939–948.
[10]
Jorge Posada, Carlos Toro, Iñigo Barandiaran, David Oyarzun, Didier Stricker, Raffaele De Amicis, Eduardo B Pinto, Peter Eisert, Jürgen Döllner, and Ivan Vallarino. 2015. Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE computer graphics and applications 35, 2 (2015), 26–40.
[11]
Fátima A Saiz, Garazi Alfaro, Iñigo Barandiaran, Sara Garcia, MP Carretero, and Manuel Graña. 2021. Synthetic Data Set Generation for the Evaluation of Image Acquisition Strategies Applied to Deep Learning Based Industrial Component Inspection Systems. (2021).
[12]
Álvaro Segura, Helen V Diez, Iñigo Barandiaran, Ander Arbelaiz, Hugo Álvarez, Bruno Simões, Jorge Posada, Alejandro García-Alonso, and Ramón Ugarte. 2020. Visual computing technologies to support the Operator 4.0. Computers & Industrial Engineering 139 (2020), 105550.
[13]
Bruno Simões, Carles Creus, María del Puy Carretero, and Álvaro Guinea Ochaíta. 2020a. Streamlining XR Technology Into Industrial Training and Maintenance Processes. The 25th International Conference on 3D Web Technology (Web3D ’20), November 9–13, 2020, Virtual Event, Republic of Korea. https://doi.org/10.1145/3424616.3424711
[14]
Bruno Simões, María del Puy Carretero, and Jorge Martínez Santiago. 2020b. Photorealism and Kinematics for Web-based CAD data. The 25th International Conference on 3D Web Technology (Web3D ’20), November 9–13, 2020, Virtual Event, Republic of Korea. https://doi.org/10.1145/3424616.3424710
[15]
Fei Tao, Fangyuan Sui, Ang Liu, Qinglin Qi, Meng Zhang, Boyang Song, Zirong Guo, Stephen C-Y Lu, and Andrew YC Nee. 2019. Digital twin-driven product design framework. International Journal of Production Research 57, 12 (2019), 3935–3953.
[16]
Sabine Waschull, Jos AC Bokhorst, Eric Molleman, and Johan C Wortmann. 2020. Work design in future industrial production: Transforming towards cyber-physical systems. Computers & industrial engineering 139 (2020), 105679.
[17]
Xun Xu. 2012. From cloud computing to cloud manufacturing. Robotics and computer-integrated manufacturing 28, 1(2012), 75–86.

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cover image ACM Conferences
Web3D '22: Proceedings of the 27th International Conference on 3D Web Technology
November 2022
129 pages
ISBN:9781450399142
DOI:10.1145/3564533
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 November 2022

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Author Tags

  1. digital twin
  2. industry 4.0
  3. web3d
  4. x3d
  5. x3dom

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Web3D '22
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Web3D '22: The 27th International Conference on 3D Web Technology
November 2 - 4, 2022
Evry-Courcouronnes, France

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