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 1434
Special Issue Editors
Interests: digital twins; smart manufacturing
Interests: digital twins; process planning
Interests: cyber-physical production systems; Internet of Things; artificial intelligence; Industry 4.0; Industry 5.0; cybersecurity; digital twin; human-centric production
Interests: Industry 4.0; Industry 5.0; digital transofrmation; advance manufacturing; production engineering; CAPP; blockchain
Special Issues, Collections and Topics in MDPI journals
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
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