Promoting digital twin technology application for process industry: A novel generation modelling platform and its implementations
Y. Z. Zhang, Wenhai Wang, Qiang Yang, Xiaoyu Tang, Wei Ruan, Yingze Li, Surong Daoerji, Xiang Zhang, Yuqi Ye, Jiawei Huang, Junjie Li, Yu Yang, Xinyao Wu, Haoran Yang, Tianyu Cao
Abstract
Abstract One key concept of Industry 4.0 is the industrial digital twin (DT)—a virtual replica of physical assets, processes, and systems. DTs optimise operations, enhance productivity, and facilitate innovation across various industries, including manufacturing, energy, healthcare, and transportation. This paper presents a multi‐domain and multi‐time scale modelling and simulation platform, featuring built‐in model libraries that represent diverse physical, chemical, and behavioural properties. A comprehensive system modelling approach and a closed‐loop industrial control system based on DTs are developed, showcasing advanced control, optimisation, and system security research capabilities. The architecture and advantages of the novel generation modelling platform are detailed, with specific applications highlighted, underscoring its contributions to the process industry.