Research On The Design And Task Scheduling Of 3D Printing Cloud Factory

Cloud manufacturing is the integration of information technology,intelligent manufacturing technology and the Internet of things technology of new manufacturing mode,to be able to access to the Internet to form the distributed manufacturing resources unified resource as a whole,manufacturing resource sharing and raising the utilization rate of resources,and a 3D printer as the main tool of distributed manufacturing individuation become a hotspot in research of cloud manufacturing.At present,relevant researches mainly focus on the establishment of 3D printing cloud platform,and there are a lot of problems worth studying in the aspects of closing the whole process manufacturing chain of 3D printing distributed manufacturing and optimizing the matching of manufacturing resources and tasks.In this paper,a 3D printing cloud factory manufacturing mode oriented to personalized distributed manufacturing is designed and a production demonstration line is set up.Meanwhile,the matching method between manufacturing resources and tasks is studied.The main contents and research results are as follows:1.On the basis of demand analysis,the overall structure of 3D printing cloud factory is established.The cloud factory is divided into two parts:the network manufacturing platform and the distributed 3D printing unmanned workshop.The function of the network manufacturing platform is designed,the technical architecture of the network manufacturing platform is analyzed,and the database and REST interface are designed.The layout of 3D printing unmanned factory is designed,and the 3D printing unmanned workshop is divided into three subsystems and its system structure and workflow are studied respectively.2.The basic concepts of MAS and UML and the modeling method of multi-agent are described.The cloud factory is decomposed into agents with different functions,and the Agent structure model,Agent organization model and Agent collaboration model are studied by adopting the modeling method based on object technology.3.Analyze the matching problem between manufacturing resources and order tasks in the cloud factory,establish the mathematical model of the problem,construct the total manufacturing cost and the maximum manufacturing time,and establish the objective optimization model.In this paper,the basic concept of genetic algorithm is introduced,and an improved NSGA2 algorithm is proposed.4.Taking an order as an example,the main functions of the cloud factory network manufacturing platform and the unmanned workshop were tested,and the load performance of the server was tested using the Tencent WeTest quality open platform.The results verified the usability and stability of the network manufacturing platform.Improved NSGA2 algorithm and adaptive weight method are implemented by Python language.The simulation data set is solved and the load performance of the algorithm is tested.The results verify the effectiveness and availability of the algorithm.