Vol. 1 No. 1 (2025)

Articles

Advancing Digital Twin Dynamics: Research and Applications

Published 2025-08-28

  • Elena Fischer

Elena Fischer
Institute for Automation and Digital Engineering, Technical University of Munich, Munich, Germany

Abstract

Digital twin technology has emerged as a transformative force across multiple industries, enabling the creation of virtual replicas of physical systems for real - time monitoring, simulation, and optimization. This paper delves into the state - of - the - art research and applications in digital twin dynamics. It comprehensively covers core technology development, validation and optimization methods, AI - driven modeling techniques, real - time data integration strategies, and interoperability aspects of cyber - physical systems. Through in - depth analysis and case studies from manufacturing, healthcare, smart cities, and aerospace industries, the paper demonstrates the potential of digital twin technology to enhance system performance, improve decision - making, and drive innovation. The research presented here not only contributes to the theoretical understanding of digital twins but also provides practical insights for their successful implementation in various industrial scenarios.

Keywords

Digital twin; Core technology; AI - driven modeling; Real - time data integration; Interoperability; Industry applications

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