• DocumentCode
    2992629
  • Title

    Ink-jet printing process modeling using neural networks

  • Author

    Pyung Moon ; Chang Eun Kim ; Dongjo Kim ; Jooho Moon ; Ilgu Yun

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea
  • fYear
    2008
  • fDate
    4-6 Nov. 2008
  • Firstpage
    1
  • Lastpage
    4
  • 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.
  • Keywords
    backpropagation; display devices; ink jet printing; neural nets; production engineering computing; semiconductor industry; color filter; drop diameter; drop velocity; error backpropagation neural networks; ink-jet printing process modeling; neural networks; response surface plot; semiconductor display industry; Color; Displays; Filters; Ink jet printing; Manufacturing industries; Manufacturing processes; Neural networks; Process control; Semiconductor device manufacture; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Manufacturing Technology Symposium (IEMT), 2008 33rd IEEE/CPMT International
  • Conference_Location
    Penang
  • ISSN
    1089-8190
  • Print_ISBN
    978-1-4244-3392-6
  • Electronic_ISBN
    1089-8190
  • Type

    conf

  • DOI
    10.1109/IEMT.2008.5507800
  • Filename
    5507800