Resource Scheduling Strategy and Process Optimization Method for Additive Manufacturing Enterprises Based on Cloud Computing

Resource Scheduling Strategy and Process Optimization Method for Additive Manufacturing Enterprises Based on Cloud Computing

Cloud manufacturing is a grand manufacturing concept aimed at reducing the waste of manufacturing resources. By borrowing the ideas of cloud computing and utilizing information technology to achieve high sharing of manufacturing resources, the core issues that both the supply and demand sides are concerned about in the cloud manufacturing process are price, product quality, and product production cycle. Therefore, this paper constructs a manufacturing process resource scheduling model that includes three elements. In order to solve the optimal solution of the model, an improved intelligent algorithm is used to solve it. The intelligent algorithm is based on the advantages of the gray wolf algorithm in solving accuracy and convergence speed. The integration of the Bat algorithm in the gray wolf algorithm improves the search ability and performance of the original gray wolf algorithm. At the same time, the gray wolf algorithm can avoid the convergence speed of the Bat algorithm from changing with the increase of iteration times. The phenomenon of slow or almost stopping. To avoid generating local optimal solutions, the accuracy of the cloud resource scheduling model and algorithm solution constructed in this paper were verified through the construction of a simulation environment.