Industry 4.0
Vol. 11 (2026), Issue 3, pg(s) 104-107

TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

Using Digital Twins in the Engineering Industry: A Comprehensive Overview

  • 1 Department of Automation and Pruduciton systems Faculty of Mechanical Engineering, Žilina, Slovakia

Abstract

Digital twin technology has rapidly evolved into a foundational pillar of modern engineering practice. By creating high-fidelity, data-driven virtual replicas of physical systems, digital twins enable continuous monitoring, predictive analytics, and advanced optimization throughout the lifecycle of assets. This extended article expands on the conceptual, technical, and practical dimensions of digital twins, providing deeper insights into architectures, data frameworks, integration strategies, real-world case studies, economic implications, and emerging research directions.

Keywords

References

  1. S. Davlatov, et al. 2026. “Integration of Digital Twin Technology and Industry 4.0 Principles for Real-Time Structural Health Monitoring in Smart Manufacturing Facilities”, in International Journal of Industrial Engineering and Management, 17(1), 1–20.
  2. K. Iranshahib, et al. 2025. “Digital twins: Recent advances and future directions in engineering fields”, in Intelligent Systems with Applications, 26, 200516.
  3. M. Gunaratne, D. Georgakopoulos and A. Banerjee. 2026. !A Digital Twins Platform for Digital Manufacturing”, in Electronics, 15(3), 583.
  4. R. Gutierrez, and J. Govea. 2025. “Digital twin integration in metalworking: enhancing efficiency and predictive maintenance”, in Frontiers in Mechanical Engineering, 11, 1655565.
  5. T. V. Babu and P. Challa. 2025. “Digital Twins in Manufacturing: A Review,” in International Journal on Science and Technology, vol. 16 (4), e-ISSN 2229-7677, DOI 10.71097/IJSAT.v16.i4.8759.
  6. A.P.A. Singh and N. Gameti. 2024. “Digital Twins in Manufacturing: A Survey of Current Practices and Future Trends,” in International Journal of Science and Research Archive, 2024, 13 (01), 1240–1250, DOI 10.30574/ijsra.2024.13.1.1705.
  7. D. Gao, et al. 2021. “Intelligent instrument fault diagnosis and prediction system based on digital twin technology,” in Journal of Physics: Conference Series, 1983 (2021) 012106, MEIE 2021, DOI 0.1088/1742-6596/1983/1/012106.
  8. S. Sopapradit and S. ae Yoosomboon. 2019. “Acceptance of Technology Digital Twin for learning in 21 st Century,” in International Journal of Computer and Information Technology vol 8 (5), ISSN 2279 – 0764.
  9. J.S. Kang. K. Chung and E. J. Hong. 2021. “Multimedia knowledge‐based bridge health monitoring using digital twin,” in Multimedia Tools and Applications 80 (26-27):1-16, DOI 10.1007/s11042-021-10649-x.
  10. R. Rolle, V. de Oliveira Martucci and E. Paciencia Godoy. 2020. “Architecture for Digital Twin implementation focusing on Industry 4.0,” in IEEE Latin America Transactions, vol. 18 (05):889-898, DOI 10.1109/TLA.2020.9082917.
  11. M.Q. Khan, M.A.H. Alvi, H.H. Nawaz and M. Umar. 2025. “Impact of Digital Twins on Real Practices in Manufacturing Industries,” in Inventions, vol 10 (6), 106. DOI 10.3390/inventions10060106.
  12. E. Green. 2023. “Digital Twins Across Manufacturing,” In book: The Digital Twin, chapter. DOI 10.1007/978-3-031-21343-4_26.
  13. https://aimultiple.com/digital-twin-applications.
  14. https://unity.com/topics/digital-twin-applications-and-use-cases.
  15. S.B. Jadhav, et. al. 2026 “Digital Twin Implementation Strategies for Complex Manufacturing Ecosystems: A Multi-Level Integration Framework,” in Journal of Engineering and Technology for Industrial Applications, ITEGAM-JETIAManaus, v.12 n.58, p. 373-380. March/April, 2026.DOI: https://doi.org/10.5935/jetia. v12i58.3071.
  16. O. Daniel and S. Lazarova-Molnar. 2025. “Automation of Decision Support in Simulation-Based Digital Twins in Manufacturing: A Survey”, in Conference: 2025 12th International Conference on Internet of Things: Systems, Management and Security (IOTSMS)At: Lyon, France, DOI 10.1109/IOTSMS68530.2025.11408584.

Article full text

Download PDF