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.
|Original language||English (US)|
|Number of pages||11|
|State||Published - 2018|
|Event||46th SME North American Manufacturing Research Conference, NAMRC 2018 - College Station, United States|
Duration: Jun 18 2018 → Jun 22 2018
Bibliographical noteFunding Information:
This project is supported by NSF Grant CMMI 1551448 entitled “EAGER/Cybermanufacturing: Architecture and Protocols for Scalable Cyber-Physical Manufacturing Systems”.
© 2018 The Author(s).
- Cloud Manufacturing
- Digital Twin
- MT Connect
- Smart Manufacturing