Research On Cloud Services Of Workshop Production And Processing Capacity In Cloud Manufacturing Environment

Cloud manufacturing is a new type of manufacturing model that provides various types of manufacturing resources through virtualization and service-oriented technology to provide users with on-demand services.It combines the cloud computing,high performance computing,intelligent science and existing information technology.Cloud manufacturing provides an idea and method for strengthening the mutual cooperation among enterprises,improving manufacturing resource utilization and enhancing the overall competitiveness.In order to promote the sharing of resources between the workshop and strengthen the cooperation between each other,this paper researches on the workshop processing capacity of the cloud services.1.For service packaging workshop production and processing capacity,based on the study of workshop production process,this paper classifies the workshop production and processing resources and analyzes the characteristic of workshop production and processing capacity.It constructs the architecture of workshop production and processing capacity based on description of the ontology of the workshop production and processing capacity,to package the workshop production and processing capacity effectively.2.In order to shorten the time for the users to choose the best service,by analyzing the characteristics of the cloud manufacturing service,from three aspects of the service attributes,manufacturing attributes and network properties,by two angles of online agreement and offline production,to build a comprehensive evaluation of cloud manufacturing services evaluation system.On this basis proposes a quantitative evaluation model based on neural network module.Firstly,the model decomposes the tasks based on the modularization idea.Then,the sub-tasks are processed by the BP network.Finally,adaptive genetic algorithm is used to optimize the integrated weights of each sub task processing module.Combined with cloud manufacturing evaluation index system and modular neural network model,cloud manufacturing services can be effectively evaluated,and providing support for users to quickly select cloud manufacturing services.3.The scheduling algorithm resources are not yet fully shared between manufacturing execution system,and it is difficult to efficiently select the appropriate scheduling algorithm for scheduling problem from the candidate scheduling resources.For solving this issue,the servitization of job shop scheduling algorithm resource in cloud manufacturing was studied.Firstly,an OWL-S-based ontology data model and publication specification of scheduling algorithm resource was given,and then a quantitative matching and recommending method based on weighted multidimensional feature fusion was presented,in order to improve the satisfaction of algorithm service requesters and the economic benefits of algorithm resource providers.Finally,through building a prototype system and using the historical data of Harbin Electrical Machinery Plant as a verification case,the results proved that the data model and recommend algorithm can effectively promote the sharing degree and selection speed of scheduling resources.