Author(s)

Xin Wan

Corresponding Author

Xin Wan

Abstract

Aiming at the problems of insufficient real-time performance and lack of interaction in traditional pipe fitting processing workshop scheduling, this paper proposes a pipe fitting processing workshop scheduling method based on digital twins. It establishes a mathematical model with the objective function of minimizing the maximum completion time and designs an improved genetic algorithm to solve it. The algorithm selects individuals using roulette combined with elite retention strategy and improves the algorithm's optimization ability and convergence speed through dynamic crossover and mutation probability during iteration. Finally, the optimized scheduling scheme based on the digital twin obtained from the solution was compared with the existing pipe fittings production scheduling scheme of the enterprise, and the indicators reflecting the production level, such as the processing cycle and production waiting time of the optimized scheduling scheme, were significantly improved and optimized. At the same time, the number of equipment used was significantly reduced when the production tasks were determined.

Keywords

Digital Twin, Flexible Job Shop Scheduling Problem, Genetic Algorithm