The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model for one type of 3D printers is designed and integrated into the core of the KRC as a shared resource. Several experiments are conducted and the results show that the CBDT has an excellent performance compared to existing methods.
L. Hu et al., "Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect," Proceedings of the 46th SME North American Manufacturing Research Conference (2018, College Station, TX), vol. 26, pp. 1193-1203, Elsevier, Jun 2018.
The definitive version is available at https://doi.org/10.1016/j.promfg.2018.07.155
46th SME North American Manufacturing Research Conference, NAMRC 46 (2018: Jun. 18-22, College Station, TX)
Mechanical and Aerospace Engineering
Intelligent Systems Center
Keywords and Phrases
Cloud Manufacturing; Digital Twin; MT Connect; Smart Manufacturing
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2018 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
01 Jun 2018