Plasma Process Classification Using Causal Discovery Technique

Kobayashi Dai, Kitsunezuka Masaki, Kataoka Yuki, Shi Jun
{"title":"Plasma Process Classification Using Causal Discovery Technique","authors":"Kobayashi Dai, Kitsunezuka Masaki, Kataoka Yuki, Shi Jun","doi":"10.1109/ISSM55802.2022.10027032","DOIUrl":null,"url":null,"abstract":"The plasma etching process for semiconductor fabrication is too complex to specify the causal structure of the mechanism especially of process variation. Therefore, prediction of etching performance is affected by correlation but not actual causal relationship to process variation. Such correlation is called pseudo correlation. In this research, we introduced the causal discovery technique to clarify the causality of the parameters in process. This method has been applied for experimental process data with consumed parts. The causal structure has been estimated reasonable and a model based on the structure have been achieved better prediction precision for process performance and parts consumption.","PeriodicalId":130513,"journal":{"name":"2022 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"1 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/ISSM55802.2022.10027032","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

The plasma etching process for semiconductor fabrication is too complex to specify the causal structure of the mechanism especially of process variation. Therefore, prediction of etching performance is affected by correlation but not actual causal relationship to process variation. Such correlation is called pseudo correlation. In this research, we introduced the causal discovery technique to clarify the causality of the parameters in process. This method has been applied for experimental process data with consumed parts. The causal structure has been estimated reasonable and a model based on the structure have been achieved better prediction precision for process performance and parts consumption.
基于因果发现技术的等离子体过程分类
半导体制造的等离子体刻蚀过程过于复杂,难以确定其机理的因果结构,特别是工艺变化的因果结构。因此,蚀刻性能的预测受工艺变化的相关性影响,而不是实际的因果关系。这种相关性被称为伪相关。在本研究中,我们引入了因果发现技术来澄清过程中参数的因果关系。该方法已应用于含废件的实验工艺数据。通过对因果结构的合理估计,建立了基于因果结构的模型,对工艺性能和零件消耗具有较好的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信