An Empirical Study on the Digital Twin System of Intelligent Production Line

Abstract

This paper focuses on the exploration of the digital twin system for intelligent production lines to address the various challenges encountered during the operation of such lines. The digital twin technology connects the physical and digital worlds by constructing virtual models, optimizing manufacturing processes such as simulating production processes, monitoring equipment operation, and rationally allocating resources. The system's architecture includes physical entity layers, data transmission layers, data layers, tools and visualization layers, and application layers. Its implementation involves modeling, data processing and analysis, real-time monitoring and prediction, optimization and simulation, and system integration and testing. The system offers diverse robot control modes, and experimental verification shows that it has excellent real-time performance, meeting the requirements for synchronized tasks in virtual and physical environments. The system integrates various functions, which help improve production efficiency, enhance safety, and optimize management processes, making significant contributions to the virtual-real joint tuning of intelligent production lines and the intelligent development of the manufacturing industry. In the future, digital twin technology will deeply integrate with other technologies and be widely applied in more fields.