Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect

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Smart Manufacturing, Digital Twin, MT Connect, Cloud Manufacturing


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.


Principal Investigator: Xiaoqing Frank Liu

Acknowledgements: This project is supported by NSF Grant CMMI 1551448 entitled “EAGER/Cybermanufacturing: Architecture and Protocols for Scalable Cyber-Physical Manufacturing Systems".