A Method for Dynamic Insertion Order Scheduling in Flexible Job Shops Based on Digital Twins

Abstract

Various production disturbances occurring in the flexible job shop production process may affect the production of the workshop, some of which may lead to the prolongation of production completion time. Therefore, a flexible job shop dynamic scheduling method based on digital twins is proposed and a dynamic scheduling framework is constructed. Compared with the traditional workshop, the digital twin-based flexible job shop can upload the relevant production data of the physical workshop to the data management center in real time, and after fusion processing the data can work cooperatively with the upper application system. Taking the dynamic disturbance of rush order insertion as an example, the dynamic scheduling of insertion order is realized based on the dynamic scheduling framework, and then the production efficiency is improved. To achieve the shortest completion time, a mathematical model for dynamic scheduling optimization is established and a genetic algorithm (GA) is applied to solve the model. Finally, a practical case is applied to show that the completion time of this algorithm is reduced by 35%, which verifies the feasibility of the proposed dynamic scheduling method.