{"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}
引用次数: 0
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.