{"title":"等离子栅蚀刻的神经网络控制:晶圆到晶圆过程控制的早期步骤","authors":"E. Rietman, S. Patel, E. Lory","doi":"10.1109/IEMT.1993.398165","DOIUrl":null,"url":null,"abstract":"A gate oxide thickness controller for a plasma etch reactor has been developed. This controller is for 0.9-/spl mu/m technology. By monitoring certain processes, signatures are fed forward into a neural network trained by the backpropagation method. It is possible to predict in real time the correct over-etch time on a wafer-by-wafer basis. Computer simulations indicate that the neural network is equivalent to humans for this task. The uniqueness of this controller is compared with a previous controller for a 1.25-/spl mu/m technology gate etch process.<<ETX>>","PeriodicalId":206206,"journal":{"name":"Proceedings of 15th IEEE/CHMT International Electronic Manufacturing Technology Symposium","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Neural network control of a plasma gate etch: Early steps in wafer-to-wafer process control\",\"authors\":\"E. Rietman, S. Patel, E. Lory\",\"doi\":\"10.1109/IEMT.1993.398165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A gate oxide thickness controller for a plasma etch reactor has been developed. This controller is for 0.9-/spl mu/m technology. By monitoring certain processes, signatures are fed forward into a neural network trained by the backpropagation method. It is possible to predict in real time the correct over-etch time on a wafer-by-wafer basis. Computer simulations indicate that the neural network is equivalent to humans for this task. The uniqueness of this controller is compared with a previous controller for a 1.25-/spl mu/m technology gate etch process.<<ETX>>\",\"PeriodicalId\":206206,\"journal\":{\"name\":\"Proceedings of 15th IEEE/CHMT International Electronic Manufacturing Technology Symposium\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 15th IEEE/CHMT International Electronic Manufacturing Technology Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMT.1993.398165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 15th IEEE/CHMT International Electronic Manufacturing Technology Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMT.1993.398165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural network control of a plasma gate etch: Early steps in wafer-to-wafer process control
A gate oxide thickness controller for a plasma etch reactor has been developed. This controller is for 0.9-/spl mu/m technology. By monitoring certain processes, signatures are fed forward into a neural network trained by the backpropagation method. It is possible to predict in real time the correct over-etch time on a wafer-by-wafer basis. Computer simulations indicate that the neural network is equivalent to humans for this task. The uniqueness of this controller is compared with a previous controller for a 1.25-/spl mu/m technology gate etch process.<>