Affiliation:
1. School of Electrical Technology, Guangdong Mechanical and Electrical Polytechnic, Guangzhou 510515, China
2. Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology, South China University of Technology, Guangzhou 510641, China
Abstract
Along with the development of new-generation information technology, digital twins (DTs) have become the most promising enabling technology for smart manufacturing. This article presents a statistical analysis of the literature related to the applications of DTs for discrete manufacturing lines, researches their development status in the areas of the design and improvement of manufacturing lines, the scheduling and control of manufacturing line, and predicting faults in critical equipment. The deployment frameworks of DTs in different applications are summarized. In addition, this article discusses the three key technologies of high-fidelity modeling, real-time information interaction methods, and iterative optimization algorithms. The current issues, such as fine-grained sculpting of twin models, the adaptivity of the models, delay issues, and the development of efficient modeling tools are raised. This study provides a reference for the design, modification, and optimization of discrete manufacturing lines.
Reference108 articles.
1. Review on Internet-of-manufacturing-things and key technologies for discrete workshop;Huang;Comput. Integr. Manuf. Syst.,2019
2. Digital twin modeling technology for solenoid assembly production line;Qiu;Comput. Integr. Manuf. Syst.,2022
3. Wan, J., Chen, B., and Wang, S. (2023). Smart Manufacturing Factory: Artificial-Intelligence-Driven Customized Manufacturing, CRC Press. [1st ed.].
4. Artificial-intelligence-driven customized manufacturing factory: Key Technologies, applications, and challenges;Wan;Proc. IEEE,2021
5. Digital Twin: Enabling Technologies, Challenges and Open Research;Fuller;IEEE Access,2020