Kinematic and dynamic modeling of mechanical systems towards Digital Twins

The development of Digital Twins has become a central topic in digital transformation, offering new possibilities for the prediction, control, and optimization of physical systems. In a general sense, a Digital Twin features real-time data exchange between a precise replica of a physical object in the virtual world, and vice versa. The virtual replica of the physical entity is usually referred to as Digital Model. A faithful representation can however affect the computational effort required by the model and consequently the data exchange in real-time. This is why, in recent years, the evolution of kinematic and dynamic models of mechanical systems in Digital Twins is essential but challenging, particularly due to the trade-off between model fidelity and computational feasibility required for real-time integration. This paper presents a systematic literature review of the methods and practices employed in modeling such systems for Digital Twin applications, focusing on tools and simulation environments used, as well as communication and computational challenges. As a final contribution, a theoretical framework is proposed as a guidance in the development of fully integrated Digital Twins for mechanical systems. • Faithful systems' modeling can be crucial for the creation of a Digital Twin. • The evolution of a Digital Model in a Digital Twin requires precise steps. • Modeling techniques together with simulation platforms have achieved great results. • Bi-directionality and real-time synchronization are fundamental. • Limitations like computational power, latency and scalability are open challenges.

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Publication Details

Journal
Results in Engineering
Published
2025-04-14
DOI
https://doi.org/10.1016/j.rineng.2025.104874
Citations
13
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
9.27
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article

Kinematic and dynamic modeling of mechanical systems towards Digital Twins

Erwin Rauch, Renato Vidoni, Veit Gufler, Chiara Nezzi
13 citations
Results in Engineering
Advanced machining processes and optimization
9.27
article

Kinematic and dynamic modeling of mechanical systems towards Digital Twins

Erwin Rauch, Renato Vidoni, Veit Gufler, Chiara Nezzi
article en
13 citations

Abstract

The development of Digital Twins has become a central topic in digital transformation, offering new possibilities for the prediction, control, and optimization of physical systems. In a general sense, a Digital Twin features real-time data exchange between a precise replica of a physical object in the virtual world, and vice versa. The virtual replica of the physical entity is usually referred to as Digital Model. A faithful representation can however affect the computational effort required by the model and consequently the data exchange in real-time. This is why, in recent years, the evolution of kinematic and dynamic models of mechanical systems in Digital Twins is essential but challenging, particularly due to the trade-off between model fidelity and computational feasibility required for real-time integration. This paper presents a systematic literature review of the methods and practices employed in modeling such systems for Digital Twin applications, focusing on tools and simulation environments used, as well as communication and computational challenges. As a final contribution, a theoretical framework is proposed as a guidance in the development of fully integrated Digital Twins for mechanical systems. • Faithful systems' modeling can be crucial for the creation of a Digital Twin. • The evolution of a Digital Model in a Digital Twin requires precise steps. • Modeling techniques together with simulation platforms have achieved great results. • Bi-directionality and real-time synchronization are fundamental. • Limitations like computational power, latency and scalability are open challenges.

Results in EngineeringVol. 26
University of Udine (IT), Free University of Bozen-Bolzano (IT)
Openalex Percentile: Top 2%
Advanced machining processes and optimization
9.27
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