{"title":"Understanding manufacturing process variation with multi-vari analysis","authors":"C. Bobbitt.","doi":"10.1109/ASMC.1990.111238","DOIUrl":null,"url":null,"abstract":"A statistical method that allows for simplicity of design and complements other statistical methods called multi-vari analysis (MVA) is described. MVA can be applied to virtually any manufacturing process. The results produced from this type of study give the engineer a good understanding of the manufacturing process. With this technique, engineers can determine manufacturing process capability and decide what steps need to be taken for further process control or improvement. The steps in performing a MVA process characterization study are given. MVA graphing and graph analysis and other uses for MVA data are discussed.<<ETX>>","PeriodicalId":158760,"journal":{"name":"IEEE/SEMI Conference on Advanced Semiconductor Manufacturing Workshop","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/SEMI Conference on Advanced Semiconductor Manufacturing Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASMC.1990.111238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A statistical method that allows for simplicity of design and complements other statistical methods called multi-vari analysis (MVA) is described. MVA can be applied to virtually any manufacturing process. The results produced from this type of study give the engineer a good understanding of the manufacturing process. With this technique, engineers can determine manufacturing process capability and decide what steps need to be taken for further process control or improvement. The steps in performing a MVA process characterization study are given. MVA graphing and graph analysis and other uses for MVA data are discussed.<>
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