Bibliographische Detailangaben
| Titel: |
Combining simulation and virtual reality for enabling interoperable digital twins in collaborative human–robot workspaces. |
| Autoren: |
Cimino, Antonio, Longo, Francesco, Nicoletti, Letizia, Solina, Vittorio |
| Quelle: |
International Journal of Production Research; Dec2025, Vol. 63 Issue 23, p9465-9501, 37p |
| Schlagwörter: |
DIGITAL twin, VIRTUAL reality, SHARED virtual environments, DIGITAL computer simulation, HUMAN-robot interaction, SYNCHRONIZATION, LABOR productivity, ERGONOMICS |
| Abstract: |
The spread of new technologies and concepts, such as Digital Twin (DT), Virtual Reality (VR) and Human–Robot Collaboration (HRC), offers unprecedented opportunities but is also posing great new challenges within the manufacturing sector. This paper presents the design and development of a novel IT solution, which includes a Real-Time Virtual Simulation (RTVS) Module and an Interactive Virtual Reality Environment (IVRE) Module, which are part of a DT Module. Its main novelty consists in being interoperable and at the same time being able to faithfully model human and robot actions, conduct ergonomic analyses and measure working times. Interoperability is guaranteed by the adoption of the FIWARE/FIROS paradigm and websockets. The proposed IT solution is implemented and validated in an assembly system of an automotive company in the context of the European project "FlExible assembLy manufacturIng with human-robot Collaboration and digital twin modEls" (FELICE). Key findings of this research work include (1) the ability to conduct numerical simulations to compare different HRC scenarios and predict productivity improvements before physical implementation; (2) efficiency assessments that help identify optimal HRC configurations to enhance operator ergonomics and (3) generally positive user feedback, with identification of directions for future developments and improvements. [ABSTRACT FROM AUTHOR] |
|
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Datenbank: |
Complementary Index |
Full Text Finder 
Nájsť tento článok vo Web of Science