Dynamic Combination Model of Cloud Manufacturing Equipment for Multi-variety and Small-batch

In the cloud manufacturing environment, the sources of manufacturing tasks and resources are more extensive. The balanced utilization of manufacturing resources is conducive to the timely completion of tasks and the good operation of the cloud system platform. Based on the network graph theory, this paper firstly constructed the cloud manufacturing process network graph based on product manufacturing BOM, described the selection constraint relationship between equipment in each process of the product, and formed the matching relationship between product processing process and manufacturing equipment. When new cloud manufacturing tasks and cloud manufacturing resources are added, or the processed and pending tasks and cloud manufacturing resources change, the cloud manufacturing dynamic matching network is updated synchronously. Secondly, considering the load of manufacturing resources, a task load queue centered on manufacturing resources was constructed. The nonlinear programming model was used to build a workshop equipment scheduling model aiming at minimizing the total processing time and cost of products. Finally, genetic algorithm is used to solve and verify the validity and accuracy of the model.