Research On Semantic Key Technology Of Manufacturing Resources Sharing Services Based On Networked Manufacturing Environment

In networked manufacturing environment, the enterprises pay close attention to the information of resource. The business process between enterprises can be regarded as a configuration and reorganization process of advantage manufacturing resources in cooperative enterprises. This process involves the resources operation including resources modeling, resources discovery, resources obtaining and resource searching and so on. To effectively manage these resources and these operations of resources, and promote manufacturing resources sharing, it becomes the core task of manufacturing resources sharing service in network manufacturing environment.The manufacturing resources sharing service platform based on the Semantic Web is designed. The semantic technology problems in resource sharing service are studied in detail in this thesis. The problems include the semantic modeling of manufacturing resource in the networked manufacturing environment, the automatic acquisition technology based on ontology, the semantic matching based on concept network and the logic reasoning based on rules. New ways are explored in order to the share and use the resource information of manufacture efficiently and resonablely, in order to obtain the efficient source sharing and to meet the needs of network manufacturing development.The following results are achieved in this thesis:(1) The research present status of manufacture source sharing home and abroad is introduced, and aimed at open question the platform of manufacture source sharing service combining with Semantic Web technology is established. The semantic technology in the platform is analyzed and the contents of the thesis and research route are determined.(2) Semantic modeling of manufacturing resources. According to the different concept of resource description of enterprises and organizations on the Internet, semantic modeling method of manufacturing resource based on the conceptual level is proposed. Manufacturing resources metadata models consist of the concept layer and metadata layer are structured by means of manufacturing resources metadata and by making full use of the existing resources description specifications and standards. So that, manufacturing resources can efficiently organized and described, and the consistency and the integrity of manufacturing resources semantic can be ensured.(3) Aimed at the main data format of manufacturing resources in internet and the main object in Web table type,ontology studying method of automatic acquisition source technology based on Web format is proposed. According to the data format of manufacturing resources knowledge on the Internet, the ontology studying method of the automatic acquisition resources based on Web form is put forward. The network resources are searched by Spider in this method. And then, the web page metadata information of table contents is extracted by means of Web page noise erasing, structuring and the documents conversion. The domain ontology is constructed automatically by mapping the concepts and the relationship among the concepts into ontology in the field of manufacturing resources.(4)In order to improve information retrieval efficiency between manufacturing resource and user retrieval conditions, weighted concept network is established firstly. Based on the weighted concept network of ontology, matching method that combines independent element similarity algorithm and structure similarity algorithm of concept network is put forward. This method is used to extract and process the concepts of user's retrieval condition based on language method, and used to calculate the concept similarity between the concepts and the manufacturing resources domain ontology. The ontology concept with highest similarity is as the entrance of concept network structure to calculate the similarity of concept structure network. The similarity is measured by the semantic distance that is calculated by the shortest path algorithm which is improved ahead, and the semantic similarity functions are constructed finally.(5) Aimed at the logic conflict problems in constructing manufacturing resource ontology, two basic reasoning mechanisms are determined based on field knowledge error detecting of description logic and based on implicit knowledge discovery reasoning of relationship. Then the reasoning model based on description logic and rules is proposed. The consistency problem in ontology is worked out by RACER reasoning based on Tableaux algorithm. In the implication knowledge discovery, based on the definition of manufacturing resources domain ontology rule, the formalization description of rules is carried out by SWRL rule language and the rule format is transformed, and then Jess reasoning based on the Rete algorithm is implemented. The ontology structure is optimized by means of automatic logic reasoning of ontology. And the knowledge level structure with reasonable logic is supplied for the ontology matching or retrieval of user's interface.