Ink-jet printing process modeling using neural networks

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

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


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.

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Ink-jet printing process modeling using neural networks'. Together they form a unique fingerprint.

Cite this