Automated optical inspection of liquid crystal display anisotropic conductive film bonding

Abstract

Anisotropic conductive film (ACF) bonding is widely used in the liquid crystal display (LCD) industry. It implements circuit connection between screens and flexible printed circuits or integrated circuits. Conductive microspheres in ACF are key factors that influence LCD quality, because the conductive microspheres’ quantity and shape deformation rate affect the interconnection resistance. Although this issue has been studied extensively by prior work, quick and accurate methods to inspect the quality of ACF bonding are still missing in the actual production process. We propose a method to inspect ACF bonding effectively by using automated optical inspection. The method has three steps. The first step is that it acquires images of the detection zones using a differential interference contrast (DIC) imaging system. The second step is that it identifies the conductive microspheres and their shape deformation rate using quantitative analysis of the characteristics of the DIC images. The final step is that it inspects ACF bonding using a back propagation trained neural network. The result shows that the miss rate is lower than 0.1%, and the false inspection rate is lower than 0.05%.