Digital Twins in Smart Manufacturing

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1444

Special Issue Editors


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Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Interests: digital twins; smart manufacturing

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Guest Editor
Department of Mechanical Engineering, School of Ocean Engineering, Harbin Institute of Technology (Weihai), Weihai, China
Interests: digital twins; process planning

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Guest Editor
Industrial Engineering and Automation (IEA), Faculty of Science and Technology, Free University of Bolzano, 39100 Bolzano, Italy
Interests: cyber-physical production systems; Internet of Things; artificial intelligence; Industry 4.0; Industry 5.0; cybersecurity; digital twin; human-centric production

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Guest Editor
Department of Mathematical and Industrial Engineering, Polytechnique Montréal, Montreal, QC, Canada
Interests: Industry 4.0; Industry 5.0; digital transofrmation; advance manufacturing; production engineering; CAPP; blockchain
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Special Issue Information

Dear Colleagues,

Everything in the future physical world will be replicated in the digital space. DTs can project physical assets or processes into the digital world to reflect the whole lifecycle process (e.g., design, production, operation and maintenance) of the real-world counterpart [1]. DTs integrate technologies such as multiphysics multiscale modeling, the Internet of Things, smart sensing, machine learning, and model-based control. DTs build a bridge between the physical world and the virtual world by mapping the entire life cycles of physical systems with real-time sensor data, maintaining complete digital trace. The digital companion of the physical world is synchronized with the physical entity for monitoring, diagnostics, prognostics, simulation and control to greatly improve product R&D, production efficiency, and PHM [2–5]. In the industrial sector, digital twins could promote the innovation in the design, production, operation and maintenance of products. Digital twins (DT) are, thus, becoming a powerful engine for smart manufacturing.

Against this background, this Special Issue will provide a platform for researchers around the world to present, discuss, and exchange their latest work in the field of “Digital Twin in Smart Manufacturing”.

Potential topics include, but are not limited to, the following:

  • Digital twin smart manufacturing;
  • Digital twin shop-floor;
  • Digital twins in product lifecycle;
  • DT in human–machine interaction;
  • DT in supply chains and logistics;
  • Modeling and simulation of digital twins;
  • Smart interconnection and interoperation for digital twins;
  • Industrial applications of digital twins.

References:

[1] Tao F, Qi Q. Make more digital twins [J]. Nature, 2019, 573(7775): 490-491.

[2] Ma X, Qi Q, Tao F. An ontology-based data-model coupling approach for digital twin [J]. Robotics and Computer-Integrated Manufacturing, 2024, 86: 102649.

[3] Ma X, Qi Q, Tao F. A Digital Twin–Based Environment-Adaptive Assignment Method for Human–Robot Collaboration [J]. Journal of Manufacturing Science and Engineering, 2024, 146(3).

[4] Xiao B, Qi Q, Tao F. Multi-dimensional modeling and abnormality handling of digital twin shop floor [J]. Journal of Industrial Information Integration, 2023, 35: 100492.

[5] Zhang H, Qi Q, Ji W, et al. An update method for digital twin multi-dimension models [J]. Robotics and Computer-Integrated Manufacturing, 2023, 80: 102481.

Dr. Qinglin Qi
Dr. Lin Wang
Dr. Matteo De Marchi
Dr. Christophe Danjou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Published Papers (1 paper)

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25 pages, 4545 KiB  
Article
A Multi-Purpose Simulation Layer for Digital Twin Applications in Mechatronic Systems
by Chiara Nezzi, Matteo De Marchi, Renato Vidoni and Erwin Rauch
Machines 2025, 13(8), 671; https://doi.org/10.3390/machines13080671 - 1 Aug 2025
Viewed by 379
Abstract
The rising complexity of industrial systems following the Industry 4.0 era involves new challenges and the need for innovative solutions. In the context of arising digital technologies, Digital Twins represent a holistic solution to overcome heterogeneity and to achieve remote and dynamic control [...] Read more.
The rising complexity of industrial systems following the Industry 4.0 era involves new challenges and the need for innovative solutions. In the context of arising digital technologies, Digital Twins represent a holistic solution to overcome heterogeneity and to achieve remote and dynamic control of cyber–physical systems. In common reference architectures, decision-making modules are usually integrated for system and process optimization. This work aims at introducing the adoption of a multi-purpose simulation module in a Digital Twin environment, with the objective of proving its versatility for different scopes. This is implemented in a relevant laboratory environment, strongly employed for the test and validation of mechatronic solutions. The paper starts from revising the common techniques adopted for decision-making modules in Digital Twin frameworks, proposing then a multi-purpose approach based on physics simulation. Performance profiling of the simulation environment demonstrates the potential of real-time-capable simulation while also revealing challenges related to computational load and communication latency. The outcome of this work is to provide the reader with an exemplary modular arrangement for the integration of such module in Digital Twin applications, highlighting challenges and limitations related to computational effort and communication. Full article
(This article belongs to the Special Issue Digital Twins in Smart Manufacturing)
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