Automobile door hinge production line dynamic scheduling method and system based on digital twinning

Abstract

The application discloses a dynamic scheduling method and system for an automobile door hinge production line based on digital twinning, and comprises the following steps: S1, collecting original production state data of the automobile door hinge production line, performing data cleaning and preprocessing on the original production state data to obtain production state data; S2, obtaining a production line digital twinning model by combining a preset mechanism model and a real-time data driving function, inputting the production state data into the production line digital twinning model for simulation initialization to obtain simulation prediction results; S3, constructing a double-loop reward intelligent agent combined with a reinforcement learning intelligent agent and a double-loop reward function, inputting the simulation prediction results into the double-loop reward intelligent agent for online learning optimization to output optimal scheduling strategy parameters; and S4, issuing the optimal scheduling strategy parameters to an execution mechanism at a bottom layer of the production line to realize real-time dynamic scheduling of the automobile door hinge production line.

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