Dynamic Optimization of the Full-link Process of Unified Production Architecture Based on Digital Twin Technology
Abstract
Information islands and response lags are common in current production systems, which seriously restrict the collaborative efficiency and dynamic optimization capabilities of each link. To solve this problem, this paper constructs a unified production architecture based on digital twin technology, realizes the digital mapping of the physical production process through a real-time state perception model driven by multi-source data, and uses the model predictive control (MPC) algorithm to dynamically schedule and optimize the full-link process. The control strategy is continuously iterated in the virtual space and fed back to the physical system to realize a closed-loop control mechanism of virtual-real synchronization. The experimental results show that the MPC optimization strategy controls the task switching time between 2.32 and 2.43 seconds, the system response delay is stabilized within 0.83 seconds, and the process response delay stability score is improved from 0.72 to 0.94. The method in this paper effectively connects the virtual-real connection of each link in the production system, realizes real-time optimization and intelligent decision-making of the whole process, and provides a feasible path for the collaborative control of intelligent manufacturing systems.References
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DOI:
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