{"title":"掩模车间的统计过程控制","authors":"Lois B. Pritchard","doi":"10.1117/12.3011922","DOIUrl":null,"url":null,"abstract":"Our industry has been hit hard by foreign competition, and it's clear we have to do something to shape up, and fast! We need data, but somehow the reams and reams of data we're known for just isn't enough anymore. Our usual methods of collecting, crunching and reporting the numbers do not do the job of improving and maintaining quality in production. We must improve quality, reduce cycle time, improve yields. It's a matter of survival. The banner some of our managers have been waving is Statistical Process Control, so it's time we learned about it and gave it a try. Statistical process control charts lend themselves quite readily to factory situations, where product may be sampled and measurements and means of the same variable plotted for each data point. A photomask shop doesn't quite work that way. Typically, the number of parts is too low for a sampling scheme to be appropriate, especially in an ebeam shop. Every part is unique, every part is measured for CD's, defects, etc., not just a sample part, and the CD required is different for every part. This paper provides a brief descriptive overview of Statistical Process Control and details the procedures appropriate for a photomask operation. The information and examples are given such that someone with little or no background in statistics may implement SPC procedures in his own mask shop, for the purpose of product quality definition and improvement.","PeriodicalId":235881,"journal":{"name":"Photomask Technology","volume":"130 1","pages":"128100B - 128100B-24"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical process control in the mask shop\",\"authors\":\"Lois B. Pritchard\",\"doi\":\"10.1117/12.3011922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our industry has been hit hard by foreign competition, and it's clear we have to do something to shape up, and fast! We need data, but somehow the reams and reams of data we're known for just isn't enough anymore. Our usual methods of collecting, crunching and reporting the numbers do not do the job of improving and maintaining quality in production. We must improve quality, reduce cycle time, improve yields. It's a matter of survival. The banner some of our managers have been waving is Statistical Process Control, so it's time we learned about it and gave it a try. Statistical process control charts lend themselves quite readily to factory situations, where product may be sampled and measurements and means of the same variable plotted for each data point. A photomask shop doesn't quite work that way. Typically, the number of parts is too low for a sampling scheme to be appropriate, especially in an ebeam shop. Every part is unique, every part is measured for CD's, defects, etc., not just a sample part, and the CD required is different for every part. This paper provides a brief descriptive overview of Statistical Process Control and details the procedures appropriate for a photomask operation. The information and examples are given such that someone with little or no background in statistics may implement SPC procedures in his own mask shop, for the purpose of product quality definition and improvement.\",\"PeriodicalId\":235881,\"journal\":{\"name\":\"Photomask Technology\",\"volume\":\"130 1\",\"pages\":\"128100B - 128100B-24\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Photomask Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.3011922\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photomask Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3011922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
我们的行业受到了外国竞争的严重冲击,显然我们必须采取措施,迅速改变现状!我们需要数据,但不知何故,我们所熟知的大量数据已经不够用了。我们惯用的收集、计算和报告数据的方法并不能提高和保持生产质量。我们必须提高质量,缩短生产周期,提高产量。这是一个事关生存的问题。我们的一些经理一直在挥舞的大旗就是统计过程控制,所以现在是我们了解并尝试一下的时候了。统计过程控制图非常适合工厂的情况,在这种情况下,可以对产品进行取样,并对每个数据点绘制同一变量的测量值和平均值。而光罩车间则不完全是这样。通常情况下,零件数量太少,不适合采用抽样方案,尤其是在电子束车间。每个零件都是独一无二的,每个零件都要测量 CD、缺陷等,而不仅仅是一个样品零件,而且每个零件所需的 CD 都不同。本文简要描述了统计过程控制,并详细介绍了适用于光罩操作的程序。本文所提供的信息和示例,可以让那些没有或几乎没有统计学背景的人在自己的掩膜车间实施 SPC 程序,以达到确定和改进产品质量的目的。
Our industry has been hit hard by foreign competition, and it's clear we have to do something to shape up, and fast! We need data, but somehow the reams and reams of data we're known for just isn't enough anymore. Our usual methods of collecting, crunching and reporting the numbers do not do the job of improving and maintaining quality in production. We must improve quality, reduce cycle time, improve yields. It's a matter of survival. The banner some of our managers have been waving is Statistical Process Control, so it's time we learned about it and gave it a try. Statistical process control charts lend themselves quite readily to factory situations, where product may be sampled and measurements and means of the same variable plotted for each data point. A photomask shop doesn't quite work that way. Typically, the number of parts is too low for a sampling scheme to be appropriate, especially in an ebeam shop. Every part is unique, every part is measured for CD's, defects, etc., not just a sample part, and the CD required is different for every part. This paper provides a brief descriptive overview of Statistical Process Control and details the procedures appropriate for a photomask operation. The information and examples are given such that someone with little or no background in statistics may implement SPC procedures in his own mask shop, for the purpose of product quality definition and improvement.