Research On Key Technologies Of Knowledge Integration And Application Supporting Networked Manufacturing For Complex Products

Networked manufacturing of complex products achieves rapid response of production processand optimal allocation of resources through collaboration and resource sharing among enterprises.The manufacturing process, which is technically complex and knowledge-intensive, includes a seriesof collaborative processes and complex decision-making activities. In order to improve the rapiddecision-making capacity in the manufacturing process, existing knowledge resources of enterprisesneed to be used effectively. In this thesis, the characteristics of manufacturing process of complexproducts, present situation of knowledge management and application in manufacturing enterprisesare analyzed. On this basis, in order to achieve agile and knowledge-based manufacturing process, theidea of organizing internal and external knowledge resource effectively and integration withmanufacturing process is put forward. The mechanism and key technologies of knowledge integrationare studied. The main contents and research findings are as follows:1. The knowledge integration mechanism of networked manufacturing system for complexproducts is studied. First, a comprehensive and detailed description of functional structure,organization, running process, resource and data management of the system is provided. Then, basedon the requirement for knowledge integration and application in networked manufacturing, the overallmodel of knowledge integration is built. Key technologies need to be addressed in knowledgeintegration are analyzed, including the integration of distributed and heterogeneous knowledge fromdifferent enterprises, associated integration among knowledge, and knowledge integration withmanufacturing process. Finally, the networked manufacturing system architecture based on knowledgeintegration is put forward, and then the working principle and characteristics of the system aredescribed.2. The integration and sharing mechanism of distributed and heterogeneous knowledge fromdifferent enterprises is studied. A hierarchical model based on multi-granularity knowledge isproposed, which is characterized by mapping among ontology, knowledge network and knowledgeelements. Manufacturing knowledge element is regarded as the basic unit of knowledge managementand use in manufacturing process. In order to provide semantic foundation for knowledge sharing,domain ontology of manufacturing task, enterprise, resource, technology and process is established,and then formalized expression of the ontology based on OWL is realized. On this basis, a knowledgeintegration method based on extended Web Service is proposed. Considering the risk and conflictduring collaborative enterprise knowledge sharing, aiming at optimizing the process, a complete information game model of knowledge sharing based on game theory is established.3. Knowledge evaluation and association analysis technology in networked manufacturing isstudied. First, the application limitations of existing method of knowledge association analysis innetworked manufacturing process are analyzed, and then applying complex network theory to theassociation analysis and evaluation of manufacturing knowledge is put forward. By abstracting theapplication process of networked manufacturing knowledge, the complex network of manufacturingknowledge is built, and its application mechanism is analyzed. On this basis, the importanceevaluation method of knowledge nodes is proposed. Utilizing the community characteristics ofnetwork, an associated knowledge cohesion algorithm based on local information is proposed. Finally,a collaborative process design instance is used to illustrate the statistics and calculations, and to verifythe accuracy and validity of the algorithm.4. Knowledge search and push technology in networked manufacturing are studied. First, theknowledge contexts of manufacturing activities are described from three dimensions. On this basis,knowledge requirement is expressed using ontology graph structure, and extended semantically withSPARQL query. For the realization of knowledge push engine, the process control structure ofknowledge push is established first, and then the semantics of manufacturing knowledge elements isdescribed using ontology graph. On this basis, a knowledge matching algorithm based on similaritycomputation of ontology graph is put forward, and proved to be effective by application to an instance.Finally, access control and visual output of push results are studied.5. Relying on the above studies and project background, the networked manufacturing system forcomplex products based on knowledge integration is developed. Development background,development ideas, technical architecture, running environment and function structure of the systemare introduced. Finally, the system is verified through a networked manufacturing example of anaerospace complex product.