Development of a dual-stage virtual metrology architecture for TFT-LCD manufacturing

Yu Chuan Su, Wen Huang Tsai, Fan Tien Cheng, Wei Ming Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Processing quality of thin film transistor-liquid crystal display (TFT-LCD) manufacturing is a key factor for production yield. In general, the processing quality of production equipment is not only related to its own manufacturing process but also affected by the process result of the previous equipment. Current proposed virtual metrology (VM) architectures are all applied to conjecture processing quality of a single stage. These single-stage VM architectures lack the ability of detecting the processing drift occur between different stages. This paper proposes a novel dual-stage VM architecture for quality conjecturing that involves two pieces of equipment. The architecture consists of two stages. In Stage I, the fore-equipment VM model is established as usual and then the rear-equipment VM model that depends on stage-I VM output is built in Stage II. An example of the proposed dual-stage VM architecture applied to two sets of TFT-LCD chemical vapor deposition (CVD) equipment is presented. Experimental results demonstrate that this dual-stage VM architecture is promising for TFT-LCD manufacturing.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Pages3630-3635
Number of pages6
DOIs
Publication statusPublished - 2008 Sep 18
Event2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA, United States
Duration: 2008 May 192008 May 23

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2008 IEEE International Conference on Robotics and Automation, ICRA 2008
CountryUnited States
CityPasadena, CA
Period08-05-1908-05-23

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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