Dynamic Management Operations Scheduling Strategy for Hybrid Manufacturing Production Line Based on Data Twin and Robotics Technology

In this paper, based on industrial robotics, a production line system based on KUKA robots is built. Aiming at the dynamic management operation scheduling problem of the robot production line, a digital twin-based production scheduling system is proposed. A two-layer progressive production scheduling strategy consisting of job sequencing and job control layers is adopted, which is combined with the production line scheduling optimization model to achieve the optimal scheduling plan for the production line. The performance tests and simulation experiments show that the workpiece conveying link in the robot production line is shortened by 15.18 s. Compared to the traditional GA algorithm, the algorithm in this paper reduces the time required to obtain the optimal scheduling solution to 35 time units, which results in faster convergence speed and better convergence results. In practice, the method in this paper generates an optimal scheduling strategy for a company’s beer packaging line.