Daisuke Kobayashi, Shunsaku Yasuda, Takashi Iuti, Shiho Ito
{"title":"Application of Natural Language Processing in Semiconductor Manufacturing","authors":"Daisuke Kobayashi, Shunsaku Yasuda, Takashi Iuti, Shiho Ito","doi":"10.1109/ISSM55802.2022.10026893","DOIUrl":null,"url":null,"abstract":"Recently, natural language processing has been making great progress in the AI field and is attracting attention. This paper describes the application of natural language processing in semiconductor manufacturing. No numerical or image data were used in any of the analyses. Using the natural language processing engine developed by SONY, we were able to analyze trends in quality troubles and extract features of manufacturing equipment from text data alone by performing various natural language processing represented by Bag-of-Ngrams and Chi-square test. By this, it can contribute to quality and productivity improvements from a different perspective.","PeriodicalId":130513,"journal":{"name":"2022 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Symposium on Semiconductor Manufacturing (ISSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM55802.2022.10026893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Recently, natural language processing has been making great progress in the AI field and is attracting attention. This paper describes the application of natural language processing in semiconductor manufacturing. No numerical or image data were used in any of the analyses. Using the natural language processing engine developed by SONY, we were able to analyze trends in quality troubles and extract features of manufacturing equipment from text data alone by performing various natural language processing represented by Bag-of-Ngrams and Chi-square test. By this, it can contribute to quality and productivity improvements from a different perspective.
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