Complex scheduling strategy for dynamic environment in digitalization- production shop

The digitalization-production shop is a very complex and dynamic production environment. It a task-oriented production organization, so its production scale and machining ability should be dynamic too. This paper presents a two-hierarchical strategy to analyze the machine load balance and machinability so as to obtain a feasible schedule with minimum total tardiness and maximum machines utilizations. In the first hierarchy, using fuzzy judgment, the substitution of equipment or combination of equipment can be found, which has similar functions with the bottleneck equipment. The tasks in the bottleneck equipment can be dispatched to the substitutable equipment in order to achieve load balance. The second hierarchy is an optimization part. A new scheduling algorithm, which integrates genetic algorithm and particle swarm optimization algorithm, is adapted to solve scheduling problem. It is more effective than genetic algorithm. The validity and feasibility of the strategy is verified by the final experiment.