The enhanced resource modeling and real-time transmission technologies for Digital Twin based on QoS considerations

Jiming Li, Yingfeng Zhang, Cheng Qian

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Digital Twin (DT) bridges the physical and virtual worlds and provides technical support to the virtualization of the real production scene. However, with the ubiquitous upgrading of the industrial infrastructure, DT systems present an independent and self-contained pattern that causes repeated constructions, stove-piped projects, and cumbersome communication. Based on the Quality of Service (QoS) considerations, this paper proposes an enabling technology framework combining semantic resource modeling with real-time industrial object transmission to improve the performance of DT and overcome these challenges. Firstly, an enhanced modeling methodology including the industrial object meta-model and the industrial object model is designed. Heterogeneous devices are modeled comprehensively, ranging from states, functions, events, interoperability, and flexibility. By formulating the unified specification to achieve standardization and generalization, workers can customize and reuse the models flexibly according to the volatile working environment. Secondly, a real-time industrial object transmission mechanism ensures high fidelity to the physical world and provides unified interfaces for value-added services. While realizing these primary communication functions in real-time, QoS factors and other advanced performances (i.e., reliability, adaptability, robustness) are fulfilled by introducing a decoupling model, a dual-channel network, and a backup strategy. Under the orchestration of all these works, a robust DT system could be developed readily. Finally, a case study is presented to verify the effectiveness of the proposed framework. The results show that interoperability, scalability, microsecond latency, and other strict requirements are realized.

Original languageEnglish
Article number102284
JournalRobotics and Computer-Integrated Manufacturing
Volume75
DOIs
StatePublished - Jun 2022

Keywords

  • Data Transmission
  • Digital Twin
  • Industrial Object Model
  • Manufacturing System
  • QoS

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