Intelligent manufacturing lines constitute a complex system characterized by the integration of multiple technologies, the intersection of various disciplines, multi-dimensional integration, and the interaction of numerous components. Currently, the internal environment of intelligent manufacturing workshops, processing technologies, and production processes all exhibit a high degree of complexity, and the diversity of underlying mechanical equipment is particularly notable. Compared to traditional manufacturing assembly lines, the process coupling between equipment in flow-type production lines is tighter and more significant. Therefore, this paper undertakes digital twin modeling of intelligent manufacturing lines from five aspects: geometry, motion, data, communication, and control. This approach aims to achieve precise and detailed mapping of the physical entity production line's processing operations.
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Zixuan Wang (2024) studied this question.
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