Research On Service Modeling And Matching Method Of Machine Tool Resources In Cloud Manufacturing Environment

Cloud manufacturing is a new manufacturing paradigm that integrates new-emerging information technology and manufacturing technology.Cloud service of machine tool resources is an important field of cloud manufacturing business.However,when providing cloud manufacturing services,machine tool resources are confronted with many problems,such as complex heterogeneous information and multiple constraints on service quality.All of those to a great degree restrict the efficiency of integration,sharing and search matching of machine tool resources in the cloud manufacturing environment.Therefore,on the basis of relevant research achievements at home and abroad,this paper explored and studied the service modeling and matching of machine tool resources in cloud manufacturing environment.Firstly,the resource service mode,resource service characteristics and attribute information composition of machine tool in cloud manufacturing environment are analyzed.Based on this,a metadata-based service modeling and encapsulation method of machine tool resources is studied to support the mapping and transformation of machine tool from physical resources to virtual resources.And then,the matching characteristics and requirements of machine tool resources in cloud manufacturing environment is analyzed,and a matching method of machine tool resource supplies and demands based on combination of function and performance is studied.The method consists of two stages: in the stage of function matching,a hierarchical matching process model of machine tool resources is established.The matching degree of each level is calculated by the matching algorithm based on semantic similarity to obtain candidate machine tool resources to meet the functional requirements of tasks.In the performance matching stage,a resource performance matching model of machine tool based on multiple quality constraints is established by grey relational analysis method to obtain a priority matching scheme to meet the performance requirements of tasks.Finally,the above research has been preliminarily tested and validated on the cloud manufacturing service platform of machine tool developed by the research group in the early stage.