{"title":"Research on the Application of CBR Technology in Intelligent Process Design System","authors":"Junli Liu, Hui Lu, Guanhui Cui, Xibin An","doi":"10.54097/592p3296","DOIUrl":null,"url":null,"abstract":"A Case-Based Reasoning (CBR) intelligent process design system is developed through Visual Studio development tools to improve the processing efficiency of mechanical parts and the recurrence rate of corporate knowledge. The key factor in improving the accuracy of case matching in the CBR system is the similarity calculation of parts. In this paper, similarity calculation models for different attribute types are presented by combining the nearest neighbor method. And the improved AHP method and matrix calculation of MATLAB are used to determine the weighting coefficient. The most similar cases are matched according to the overall similarity of the cases and the set threshold, and the method is applied to the intelligent process design of shafts. The results show that this method is conducive to shortening the development cycle and quickly responding to the market, which provides a reference for intelligent manufacturing of mechanical parts.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":" 23","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54097/592p3296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A Case-Based Reasoning (CBR) intelligent process design system is developed through Visual Studio development tools to improve the processing efficiency of mechanical parts and the recurrence rate of corporate knowledge. The key factor in improving the accuracy of case matching in the CBR system is the similarity calculation of parts. In this paper, similarity calculation models for different attribute types are presented by combining the nearest neighbor method. And the improved AHP method and matrix calculation of MATLAB are used to determine the weighting coefficient. The most similar cases are matched according to the overall similarity of the cases and the set threshold, and the method is applied to the intelligent process design of shafts. The results show that this method is conducive to shortening the development cycle and quickly responding to the market, which provides a reference for intelligent manufacturing of mechanical parts.