{"title":"Six-Sigma Based Performance Verification in Early Development of Automatic Test Equipment","authors":"Madhu Kilari, Qiyu Huang, T. Jin","doi":"10.1109/SSIRI.2009.13","DOIUrl":null,"url":null,"abstract":"This paper proposes a Six-Sigma based performance verification approach to characterizing the channel voltage variation of automatic testing equipment (ATE). The purpose of the performance verification is to determine the level of measurement uncertainty in ATE voltage channels. Six-Sigma tools may not be directly applied to the measurement data when the underlying distribution is highly skewed. A solution is to appropriately transform the original data set into a new domain such that the transformed data can be approximated by the normal distribution. Then the Six-Sigma tools can be adopted to quantify the lower and upper limits of the random voltage signals. The proposed method was successfully applied to characterize the noise window, or the voltage variation limits, on the broadband AC (BBAC) instrument.","PeriodicalId":196276,"journal":{"name":"2009 Third IEEE International Conference on Secure Software Integration and Reliability Improvement","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third IEEE International Conference on Secure Software Integration and Reliability Improvement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSIRI.2009.13","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
This paper proposes a Six-Sigma based performance verification approach to characterizing the channel voltage variation of automatic testing equipment (ATE). The purpose of the performance verification is to determine the level of measurement uncertainty in ATE voltage channels. Six-Sigma tools may not be directly applied to the measurement data when the underlying distribution is highly skewed. A solution is to appropriately transform the original data set into a new domain such that the transformed data can be approximated by the normal distribution. Then the Six-Sigma tools can be adopted to quantify the lower and upper limits of the random voltage signals. The proposed method was successfully applied to characterize the noise window, or the voltage variation limits, on the broadband AC (BBAC) instrument.