{"title":"Research on customer requirements processing model of mass customization design","authors":"Tao Xi, Lijing Wang, Minghua Shi","doi":"10.1109/MACE.2010.5536528","DOIUrl":null,"url":null,"abstract":"According to the actual characteristics of the customer requirements information in mass customization design, the requirements information processing model is established based on fuzzy set, rough set and Support vector machine theory of effective. Firstly, the discrete numerical processing of semantic attributes, fuzzy-based information and continuous values in customer demands are carried out with fuzzy set theory. Then the rough set theory is used to reduce attribute and extract rule for a large number of redundant information. Finally, the use of support vector machine theory, reduction properties of the requirements and functional characteristics of products are carried out regression analysis. Acustomization design case of engineering machinery equipment is developed to illustrate that the model can effectively handle the semantic, fuzzy-based and requirements information extraction and function quality mapping of redundancy information in customer requirements.","PeriodicalId":6349,"journal":{"name":"2010 International Conference on Mechanic Automation and Control Engineering","volume":"38 1 1","pages":"6168-6171"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Mechanic Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACE.2010.5536528","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
According to the actual characteristics of the customer requirements information in mass customization design, the requirements information processing model is established based on fuzzy set, rough set and Support vector machine theory of effective. Firstly, the discrete numerical processing of semantic attributes, fuzzy-based information and continuous values in customer demands are carried out with fuzzy set theory. Then the rough set theory is used to reduce attribute and extract rule for a large number of redundant information. Finally, the use of support vector machine theory, reduction properties of the requirements and functional characteristics of products are carried out regression analysis. Acustomization design case of engineering machinery equipment is developed to illustrate that the model can effectively handle the semantic, fuzzy-based and requirements information extraction and function quality mapping of redundancy information in customer requirements.