The application discloses an AI-based intelligent factory dynamic production scheduling optimization method and
system, and belongs to the technical field of factory dynamic production scheduling, and the method comprises the following steps: acquiring and integrating the working states of various types of equipment in the factory, the inventory location states of different materials, manual data,
production order states, process
route requirements, the plan and
completion time of each process, and the delivery period requirements of customers; combining the supply chain
material data, the factory storage space, the equipment switching cost, the production rules, the order process dependency relationship, and the production target, and generating an initial production scheduling plan through an AI optimization
algorithm; the application generates an initial scheduling plan by acquiring and integrating multiple types of production data, monitors dynamic events, evaluates multiple schemes, selects an optimal scheme through economic model evaluation, and realizes production refinement, dynamic response, and benefit optimization.