Harnessing Data Engineering for Intelligent Manufacturing: Digital Twin–Algorithm Fusion and Applications

Abstract

 With the advancement of Industry 4.0, intelligent manufacturing has become an inevitable trend in the development of the manufacturing sector. The integration of digital twins and intelligent algorithms offers new avenues for optimizing smart manufacturing systems. This paper first elucidates the background and significance of this integration, analyzing its importance and potential value in optimizing smart manufacturing systems. It then explores the concepts and reference architectures of digital twins and smart manufacturing optimization, including conceptual evolution and reference architecture composition. It then elaborates on key technological systems such as data-driven modeling, multimodal perception, real-time synchronization, intelligent decision-making, distributed computing, and security detection. The paper examines the application of digital twin-intelligent algorithm integration in discrete production lines, process manufacturing, major equipment manufacturing, and collaborative robot clusters, analyzes current challenges and bottlenecks, and concludes with an outlook on future development trends.