Research On Cutting Tool Resource Service System Based On Ontology And CBR

The manufacturing resource service platform is an important means for the manufacturing industry to transform from traditional production mode to digital,intelligent and service-oriented.With the continuous increase of platform service types and number of services,how to help platform users recommend the services they need from numerous services It is a problem that the service platform needs to solve.The traditional service platform relies on service providers and service demanders to match the description of service functions and service requirements,but it relies on the accuracy of the description and the trust of users,and cannot intuitively help users make further selections of services.In the process of using the platform,a large number of service cases can be accumulated.If service cases that meet the needs of users can be recommended and displayed,it will undoubtedly help users choose and arrange services.Cutting tools are important equipment in the manufacturing industry,which has a significant impact on product quality and production costs.However,there are few related researches on tool resource services,so the application of tool resource service cases has very important practical significance.In view of this,this article takes the tool resource service as the research object,based on case reasoning(CBR)and ontology(Ontology)technology,with the purpose of recommending tool resource service cases to users,the case representation and case retrieval are studied,and based on B/ S architecture developed a prototype system.The main research content and results of this thesis are as follows:(1)Representation of manufacturing resource service case based on ontology.Based on the definition and classification of tool resource services,this paper establishes the representation method of manufacturing resource service domain ontology and tool resource service cases based on ontology technology with the help of Protégé ontology editing software.In order to improve the retrieval speed of ontology and facilitate management,Neo4 j is adopted.As the storage medium of the ontology,graph data provides necessary support for case retrieval.(2)Proposal of retrieval model.In order to improve the traditional case reasoning model that only focuses on similarity,the recommended case may not be the optimal case.On the basis of the semantic-attribute two-tier retrieval architecture,combined with the quality of service and multi-criteria decision-making technology(MCDM),the semantic-The attribute-service quality three-tier retrieval architecture can better meet the needs of users.(3)Improvement of similarity calculation method.In the semantic retrieval stage,in order to improve the shortcomings of the ontology-based structural similarity algorithm relying on the lack of scalability of the ontology structure,this paper combines the character-based edit distance similarity algorithm with it,and proposes a comprehensive semantic similarity algorithm.In the attribute retrieval stage,the grey correlation algorithm is applied to the attribute similarity calculation,and the subjective and objective comprehensive weight calculation method based on the ZBWM and CRITIC methods is proposed.In the quality of service stage,in order to improve the problem that the solution of the traditional ideal point method is far away from the optimal solution,the VIKOR method is used in the service ranking based on the quality of service(Qo S).Finally,examples are used to verify the rationality and feasibility of the proposed methods at each stage.(4)According to the methods mentioned above,the prototype system is designed and developed based on the B/S architecture,and the system interface is briefly introduced.