Research On Knowledge Semantic Management Technology In Closed-Loop Lifecycle Management System

The closed-loop lifecycle management(CL2M)concept is proposed and established which aims to use the Internet of things,large data,cloud computing and other new technologies to cross different systems and organizations,tracking,access to product lifecycle data,to achieve closed-loop product information flow,improve the efficiency of business operations,to provide users with better service.Currently,in the CL2M system,the information obtained at different stages of life is independent of each other and expressed in different ways,these hinder the sharing and reuse of knowledge.At the same time,the semantic information of product knowledge isn’t extracted fully,lack of effective knowledge acquisition program,which greatly reduces the utilization of knowledge.For these issues,the key problems of knowledge semantic management are studied deeply,and the specific algorithms and solutions are provided.The main work is as follows:1.The characteristics of knowledge in CL2M system are analyzed,the demands of knowledge semantic management are elaborated in detail;the product data and knowledge management technology in CL2M system is introduced and its shortcomings are analyzed.At last,based on analysis of the characteristics and the functions of knowledge semantic management,the knowledge semantic management architecture is designed.2.Based on the ontology model,the multi-dimensional and multi-level knowledge integration framework is constructed for the CL2M system,to realize product knowledge representation.On this basis,the document semantic vector and the ontology semantic vector extraction and matching algorithms are designed.To the knowledge semantic space as the semantic annotation result of knowledge,the knowledge multidimensional annotation is completed in the knowledge integration framework in CL2M system.3.The knowledge demands model is constructed from multiple perspectives.Based on the ontology similarity calculation method,the demand model and the knowledge ontology matching algorithm is designed,and the product knowledge semantic map is constructed by using knowledge ontology and semantic space.The key knowledge nodes are defined on the knowledge semantic map,by introducing the complex network theory method to analyze the internal structure of the knowledge semantic map,the key knowledge nodes extraction method and the importance judgment scheme are designed,to guide the user knowledge browsing.4.The knowledge semantic management platform of CL2M system is designed,the main functions of knowledge semantic management platform are implemented by procedures,the network characteristic parameters of the knowledge semantic map are calculated.Finally,the low temperature plasma equipment system is used as the applied research object.Through the semantic annotation algorithm and the similarity matching algorithm is used to test and compare,the small-world network and the scale-free network of the knowledge semantic map are verified,extract key knowledge nodes and test their importance,and the validity of the knowledge acquisition and presentation scheme is proved.Based on CL2M system knowledge semantic management technology research,and then further development and application.Extensive and thorough mining product knowledge semantic information that improve the knowledge utilization,achieve product knowledge in the whole lifecycle within the sharing and reuse.