{"title":"Uniform design method to finding the optimal parameters for machine roughing","authors":"Y. Cai, J. Chou","doi":"10.1109/ICSSE.2016.7551639","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to use uniform design method for finding the optimal parameters of a rough machining process. The method can reduce the consume time and cost in the adjusting optimal parameters of the machining process by experience. According to the experiments and the signal-to-noise ratio (SNR) of the uniform design method, the regression relation between input parameters and output performance can be obtained. Furthermore, we can find the optimal parameters from the regression equation. Experimental results prove that the proposed method can indeed effectively reduce time and cost to find the optimal parameters.","PeriodicalId":175283,"journal":{"name":"2016 International Conference on System Science and Engineering (ICSSE)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2016.7551639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The purpose of this paper is to use uniform design method for finding the optimal parameters of a rough machining process. The method can reduce the consume time and cost in the adjusting optimal parameters of the machining process by experience. According to the experiments and the signal-to-noise ratio (SNR) of the uniform design method, the regression relation between input parameters and output performance can be obtained. Furthermore, we can find the optimal parameters from the regression equation. Experimental results prove that the proposed method can indeed effectively reduce time and cost to find the optimal parameters.