Open Access

ARTICLE

Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

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

1 Process Research Institution, China National Heavy Duty Truck Group Co., Ltd., Jinan, 250100, China
2 Transmission Factory, China National Heavy Duty Truck Group Co., Ltd., Jinan, 250100, China
3 5G Intelligent Manufacturing Research Center, Institute of Marine Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China
4 Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

* Corresponding Author: Yahui Zhang. Email:

(This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)

Computer Modeling in Engineering & Sciences 2024, 139(3), 3233-3253. https://doi.org/10.32604/cmes.2023.030773

Received 21 April 2023; Accepted 14 June 2023; Issue published 11 March 2024

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, this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line. Firstly, the DT-based system architecture is designed, and the DT model is created by constructing the visualization model, logic model, and data model of the assembly line. Then, a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line. Eventually, some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

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