A Digital Twin Case Study on Prefabricated Component Factory for Offsite Manufacturing of Buildings
Year: 2025
Type: conference-paper
Abstract: With the transformation of the construction manufacturing industry, off-site manufacturing technologies are gradually becoming mainstream. The existing digital systems of Prefabricated Component (PC) factories have problems such as incomplete presentation, inaccurate expression of physical entities in the information space, and weak real-time synchronization ability. To address these issues, we propose a digital twin system architecture applied to PC factories, which is divided into the physical entity layer, the digital twin entity layer, and the user entity layer. On this basis, relying on the Hannan PC Factory of China Construction Third Engineering Bureau Science and Technology Innovation Industry Development Co., Ltd., and based on physical systems such as the Internet of Things (IoT), Programmable Logic Controllers (PLC), central control systems, and Manufacturing Execution Systems (MES), a complete digital twin system has been designed and implemented. Through the association and mapping between digital twin virtual entities and physical entities, staff can monitor the production operation status in a realistic three-dimensional visual way in real time and make decisions. The actual operation effect has verified the effectiveness of the system framework, solved the problems that traditional PC factory digital systems cannot comprehensively present and accurately express the physical entities of PC factories and synchronize the production process in real time, and can lay a solid foundation for the subsequent dynamic prediction and decision optimization of prefabricated component production facilities.
Authors: Zhenyuan Tan, Ming Tu, Xinglin He, Bingyong Chen, Yishi Zhao, Jianga Shang
Institution: China University of Geosciences
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413845222