Xianfeng Cao¹, Meihua Yao², Yahui Zhang^3,*, Xiaofeng Hu⁴, Chuanxun Wu³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773

Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control logic, and real-time data interaction,… More > Graphic Abstract

Ying Bai^1,*, Xiaoti Ren², Hong Li¹

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2999-3018, 2023, DOI:10.32604/iasc.2023.040124

Abstract The combination of the Industrial Internet of Things (IIoT) and digital twin (DT) technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance. However, conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information. The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model. In this paper, a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state. Firstly, a global real-time feedback and the dynamic adjustment mechanism is established by combining DT-IIoT… More >