Research Advancements in Digital Twin Technology for Smart Manufacturing

Main Article Content

Loso Judijanto
Arnes Yuli Vandika

Abstract

This study presents a comprehensive bibliometric analysis of research developments in Digital Twin (DT) technology within the domain of smart manufacturing. Drawing on Scopus-indexed publications from 2010 to 2024, the study explores the growth patterns, thematic structures, institutional contributions, collaborative networks, and emerging research trends using VOSviewer. The findings reveal a sharp increase in publication volume, particularly in 2024, indicating growing academic and industrial interest. China dominates the research landscape in terms of both institutional productivity and international collaboration, followed by India and the United States. Keyword co-occurrence analysis identifies “smart manufacturing,” “digital twin,” and “industry 4.0” as core themes, with increasing emphasis on artificial intelligence, optimization, collaborative robots, and Industry 5.0 in recent years. Co-authorship and country collaboration maps illustrate dense scholarly networks centered around prominent authors and regions. Despite significant progress, the study identifies gaps in real-world implementation, standardization, and ethical considerations. These insights offer valuable direction for future interdisciplinary research and policy strategies aimed at integrating DT technologies into next-generation manufacturing ecosystems.

Article Details

How to Cite
Judijanto, L., & Vandika, A. Y. (2025). Research Advancements in Digital Twin Technology for Smart Manufacturing. The Eastasouth Journal of Information System and Computer Science, 2(03), 205–218. https://doi.org/10.58812/esiscs.v2i03.548
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Articles

References

L. Li, B. Lei, and C. Mao, “Digital twin in smart manufacturing,” J. Ind. Inf. Integr., vol. 26, p. 100289, 2022.

P. Evangeline, “Digital twin technology for ‘smart manufacturing,’” in Advances in computers, Elsevier, 2020, pp. 35–49.

F. Tao, M. Zhang, and A. Y. C. Nee, Digital twin driven smart manufacturing. Academic press, 2019.

L. Lattanzi, R. Raffaeli, M. Peruzzini, and M. Pellicciari, “Digital twin for smart manufacturing: A review of concepts towards a practical industrial implementation,” Int. J. Comput. Integr. Manuf., vol. 34, no. 6, pp. 567–597, 2021.

M. Soori, B. Arezoo, and R. Dastres, “Digital twin for smart manufacturing, A review,” Sustain. Manuf. Serv. Econ., vol. 2, p. 100017, 2023.

Q. Qi, F. Tao, Y. Zuo, and D. Zhao, “Digital twin service towards smart manufacturing,” Procedia Cirp, vol. 72, pp. 237–242, 2018.

Y. Wang, X. Kang, and Z. Chen, “A survey of digital twin techniques in smart manufacturing and management of energy applications,” Green Energy Intell. Transp., vol. 1, no. 2, p. 100014, 2022.

B. He and K.-J. Bai, “Digital twin-based sustainable intelligent manufacturing: a review,” Adv. Manuf., vol. 9, no. 1, pp. 1–21, 2021.

G. Shao, S. Jain, C. Laroque, L. H. Lee, P. Lendermann, and O. Rose, “Digital twin for smart manufacturing: the simulation aspect,” in 2019 Winter Simulation Conference (WSC), IEEE, 2019, pp. 2085–2098.

Q. Liu et al., “Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system,” J. Manuf. Syst., vol. 58, pp. 52–64, 2021.

J. Leng, D. Wang, W. Shen, X. Li, Q. Liu, and X. Chen, “Digital twins-based smart manufacturing system design in Industry 4.0: A review,” J. Manuf. Syst., vol. 60, pp. 119–137, 2021.

J. Wang, L. Ye, R. X. Gao, C. Li, and L. Zhang, “Digital Twin for rotating machinery fault diagnosis in smart manufacturing,” Int. J. Prod. Res., vol. 57, no. 12, pp. 3920–3934, 2019.

S. Ma, W. Ding, Y. Liu, S. Ren, and H. Yang, “Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries,” Appl. Energy, vol. 326, p. 119986, 2022.

C. Zhuang, J. Liu, and H. Xiong, “Digital twin-based smart production management and control framework for the complex product assembly shop-floor,” Int. J. Adv. Manuf. Technol., vol. 96, pp. 1149–1163, 2018.

L. Ante, “Digital twin technology for smart manufacturing and industry 4.0: A bibliometric analysis of the intellectual structure of the research discourse,” Manuf. Lett., vol. 27, pp. 96–102, 2021.

V. Damjanovic-Behrendt and W. Behrendt, “An open source approach to the design and implementation of Digital Twins for Smart Manufacturing,” Int. J. Comput. Integr. Manuf., vol. 32, no. 4–5, pp. 366–384, 2019.

J. Lee, M. Azamfar, J. Singh, and S. Siahpour, “Integration of digital twin and deep learning in cyber‐physical systems: towards smart manufacturing,” IET Collab. Intell. Manuf., vol. 2, no. 1, pp. 34–36, 2020.

J. Cheng, H. Zhang, F. Tao, and C.-F. Juang, “DT-II: Digital twin enhanced Industrial Internet reference framework towards smart manufacturing,” Robot. Comput. Integr. Manuf., vol. 62, p. 101881, 2020.

G. Mylonas, A. Kalogeras, G. Kalogeras, C. Anagnostopoulos, C. Alexakos, and L. Muñoz, “Digital twins from smart manufacturing to smart cities: A survey,” Ieee Access, vol. 9, pp. 143222–143249, 2021.

V. Warke, S. Kumar, A. Bongale, and K. Kotecha, “Sustainable development of smart manufacturing driven by the digital twin framework: A statistical analysis,” Sustainability, vol. 13, no. 18, p. 10139, 2021.

F. Tao, H. Zhang, A. Liu, and A. Y. C. Nee, “Digital twin in industry: State-of-the-art,” IEEE Trans. Ind. informatics, vol. 15, no. 4, pp. 2405–2415, 2018.

F. Tao, J. Cheng, Q. Qi, M. Zhang, H. Zhang, and F. Sui, “Digital twin-driven product design, manufacturing and service with big data,” Int. J. Adv. Manuf. Technol., vol. 94, pp. 3563–3576, 2018.

A. Fuller, Z. Fan, C. Day, and C. Barlow, “Digital twin: Enabling technologies, challenges and open research,” IEEE access, vol. 8, pp. 108952–108971, 2020.

M. Liu, S. Fang, H. Dong, and C. Xu, “Review of digital twin about concepts, technologies, and industrial applications,” J. Manuf. Syst., vol. 58, pp. 346–361, 2021.

Q. Qi and F. Tao, “Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison,” Ieee Access, vol. 6, pp. 3585–3593, 2018.

A. Rasheed, O. San, and T. Kvamsdal, “Digital twin: Values, challenges and enablers from a modeling perspective,” IEEE access, vol. 8, pp. 21980–22012, 2020.

D. Gu, X. Shi, R. Poprawe, D. L. Bourell, R. Setchi, and J. Zhu, “Material-structure-performance integrated laser-metal additive manufacturing,” Science (80-. )., vol. 372, no. 6545, p. eabg1487, 2021.

Q. Qi et al., “Enabling technologies and tools for digital twin,” J. Manuf. Syst., vol. 58, pp. 3–21, 2021.

F. Tao and M. Zhang, “Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing,” IEEE access, vol. 5, pp. 20418–20427, 2017.

F. Tao et al., “Digital twin-driven product design framework,” Int. J. Prod. Res., vol. 57, no. 12, pp. 3935–3953, 2019.