Pyung Moon, C. E. Kim, Dongjo Kim, Jooho Moon, I. Yun
{"title":"喷墨印刷过程的神经网络建模","authors":"Pyung Moon, C. E. Kim, Dongjo Kim, Jooho Moon, I. Yun","doi":"10.1109/IEMT.2008.5507800","DOIUrl":null,"url":null,"abstract":"Inkjet printing process is recently interested in semiconductor display industry because of the advantages such as low-cost, ease of manufacture and diversity of applications. In this paper, the models of inkjet printing process for color filter using displays are investigated using the error back propagation neural networks. The input factors are extracted by prescreening among controlled process variables. The drop diameter and drop velocity are extracted as the output responses to characterize inkjet printing process. The modeling results for the drop diameter and the drop velocity are investigated based on the training and the testing errors. The proposed neural network models are then analyzed using the response surface plot.","PeriodicalId":151085,"journal":{"name":"2008 33rd IEEE/CPMT International Electronics Manufacturing Technology Conference (IEMT)","volume":"290 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ink-jet printing process modeling using neural networks\",\"authors\":\"Pyung Moon, C. E. Kim, Dongjo Kim, Jooho Moon, I. Yun\",\"doi\":\"10.1109/IEMT.2008.5507800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inkjet printing process is recently interested in semiconductor display industry because of the advantages such as low-cost, ease of manufacture and diversity of applications. In this paper, the models of inkjet printing process for color filter using displays are investigated using the error back propagation neural networks. The input factors are extracted by prescreening among controlled process variables. The drop diameter and drop velocity are extracted as the output responses to characterize inkjet printing process. The modeling results for the drop diameter and the drop velocity are investigated based on the training and the testing errors. The proposed neural network models are then analyzed using the response surface plot.\",\"PeriodicalId\":151085,\"journal\":{\"name\":\"2008 33rd IEEE/CPMT International Electronics Manufacturing Technology Conference (IEMT)\",\"volume\":\"290 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 33rd IEEE/CPMT International Electronics Manufacturing Technology Conference (IEMT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMT.2008.5507800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 33rd IEEE/CPMT International Electronics Manufacturing Technology Conference (IEMT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMT.2008.5507800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ink-jet printing process modeling using neural networks
Inkjet printing process is recently interested in semiconductor display industry because of the advantages such as low-cost, ease of manufacture and diversity of applications. In this paper, the models of inkjet printing process for color filter using displays are investigated using the error back propagation neural networks. The input factors are extracted by prescreening among controlled process variables. The drop diameter and drop velocity are extracted as the output responses to characterize inkjet printing process. The modeling results for the drop diameter and the drop velocity are investigated based on the training and the testing errors. The proposed neural network models are then analyzed using the response surface plot.