Study of UPI Cell Particle Defects Improvement Using Vertical Dish Brush

• Main Authors: Wang,Chi-Hsiung, 王際雄
• Other Authors: Cheng,Stone
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/62104466862072895193

碩士 === 國立交通大學 === 工學院精密與自動化工程學程 === 104 === This study explored the improvement of substrate cleaning process before Polyimide film coating in the thin-film transistor liquid crystal display (TFT-LCD) production line. An entire batch of TFT-LCD panel was returned by customer caused by the excessive number of 8%–20% cell particles (CP) defects. Profile analysis process of CP types was conducted on the defected products by question and answer (Q&;A) map and fishbone diagram to assign scores for various defect types. Through the analysis of CP, the defects were categorized into two types: (1) under polyimide (UPI), which refers to particle defects under the polyimide (PI) layer; or (2) over polyimide (OPI), which refers to particle defects above the PI layer. Additionally, the yield loss statistic showed that the OPI type accounted for 17.3% of yield loss, whereas the UPI type accounted for 82.7% of yield loss, among which dirt particles on the substrate surface before PI processing accounted for 68.56% of the overall yield loss of the UPI type. The main cause of these particle defects was due to the failure of cleaning the peripheral machines to prevent dirt from getting on the substrate surface before coating the PI fluid onto the glass substrate surface (TFT or CF), which causing an uneven coverage of PI fluid on the substrate surface during PI film coating, and resulting in poor alignment. Furthermore, because the UPI-type defects were located below the PI layer, the dirt could not be deleted during the post-process cleaning, and reworking of panel was not cost-effective. To improve the pre-PI process cleaning ability, this study replaced the original horizontal brush wheels with standing (vertical) brush wheels, and used the Taguchi method to optimize the process parameters (forward–reverse brushing method, brush wheel speed, brush wheel pressure, and convey speed). The optimized parameters were applied to the substrate cleaning process, and the yield loss was reduced from 8%~20% to 2%~6%.