Research And Implementation On Collaborative Optimization Management Method For Cloud Manufacturing Resorces

Cloud Manufacturing(CM)combines cloud computing and manufacturing technology,and realizes "dispersed resources and centralized management" through "manufacturing cloud",which is an important way to solve the problem of "big but not strong" in China's manufacturing industry,give full play to the efficiency of China's existing manufacturing resources,and realize the intelligent upgrading of traditional manufacturing industry.The cloud manufacturing platform connects idle manufacturing capabilities with user demand through collaborative management and optimized matching of manufacturing resources.The level of collaborative management and the quality of matching scheme will have a decisive impact on the operating efficiency and service quality of the platform.In the process of resource matching,the existing cloud manufacturing platform attaches more importance to technology than management,and fails to effectively manage and utilize the massive historical matching data stored in the cloud,resulting in a large amount of data redundancy and resource waste.In view of this,in order to improve the resource management level of the cloud manufacturing platform and fully explore the potential of historical matching data,this paper studies the collaborative optimization management method of cloud manufacturing resources.Firstly,based on the basic theory of cloud manufacturing resource management,the problem of collaborative optimization management of cloud manufacturing resources was analyzed,and a composite collaborative mechanism system of cloud manufacturing resource management was established from three dimensions of manufacturing tasks' goals,time and resources,and the overall implementation framework of collaborative optimization management of cloud manufacturing resources was designed.Secondly,based on the classification of manufacturing resources,the perception methods of various kinds of resource information were determined,and the ontology modeling of manufacturing resources was carried out based on the formal description model of the resources,which realizes the virtualization and service-oriented encapsulation of resources.The formal definition of the tasks is given,and the publishing of cloud manufacturing resources and tasks is realized through database connection.Thirdly,for the matching problem of similar resource groups in cloud manufacturing,a genetic algorithm model was designed to find the shortest completion time,and massive historical data was used to train the model.The initial population of the algorithm model was optimized through the transformation and mapping of historical matching schemes,and the results of different initial population generation strategies are compared.With the solution results,an optimized solution to the resource matching problem was obtained.Finally,the resource management system of cloud manufacturing platform was designed based on project management software P6.Data interaction and collection among different databases are used to store and operate manufacturing resources and task data,and management functions of the system for users,resources and projects are built by using P6.The resource matching optimization algorithm is called to find the resource matching optimization scheme and the information related to resource matching and task execution is shared within the LAN.