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Optimal Yield Rate in ACF Cutting Process of TFT-LCD Module Using Orthogonal Particle Swarm Optimization Based on Response Surface Design
ARTICLE

, , Department of Mechanical and Automation Engineering National Kaohsiung First University of Science and Technology Nantze, Taiwan

Journal of Applied Research and Technology Volume 12, Number 6, ISSN 1665-6423 Publisher: Elsevier Ltd

Abstract

Anisotropic Conductive Film (ACF) is essential material in LCM (Liquid Crystal Module) process. It is used in bonding process to make the driving circuit conductive. Because the price of TFT-LCD is getting lower than before in recent years, the ACF has relatively higher cost ratio. The conventional long bar ACF cutting unit is changed into short bar ACF cutting unit in new bonding technology. However, the new type machine was not optimized in process control and mechanical design. Therefore, the failure rate of new ACF cutting process is much higher than the one of the conventional process. This wastes the ACF material and rework cost is considerably large. How to make the manufacturing cost down effectively and promote the product quality is the main issue to maintain competition capability for the product. Therefore, the orthogonal particle swarm optimization (OPSO) is used to analyze the optimal design problem. The ACF cutting yield rate is selected to be objective function for optimization. The quality characteristic function for yield rate is used in orthogonal particle swarm optimization. Three control factors such as plasma clean speed, ACF peeling speed and ACF cutter spring setting are selected to study the effect of the yield rate. Results show that the proposed method can provide good optimal solution to improve the ACF cutting process for TFTLCD manufacturing process.

Citation

Kuo, J.L. & Cheng, M.T. (2014). Optimal Yield Rate in ACF Cutting Process of TFT-LCD Module Using Orthogonal Particle Swarm Optimization Based on Response Surface Design. Journal of Applied Research and Technology, 12(6), 1165-1175. Elsevier Ltd. Retrieved April 20, 2021 from .

This record was imported from Journal of Applied Research and Technology on January 29, 2019. Journal of Applied Research and Technology is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/S1665-6423(14)71675-X

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