Serious pattern defects and particles co-exist on the glass and only a few defects can cause serious quality problem. Now, if there would be a way to classify the defect by its potential lethality, it would be useful to control the product quality and loss of review time. This paper presents a method to classify the defect by using reviewing images. First, several defect types were investigated to develop an algorithm. In next, efficiency of the algorithm was verified in a plant. The result was good enough to utilize the information of classified defect type. Finally, the algorithm was applied to remove the information of trivial defects. The result was good to increase a throughput of whole process under little risk.
LCD(Liquid Crystal Display) became one of the most popular display devices in these days. The TFT(Thin Film Transistor) substrate is the key part of active matrix LCD. TFT is an electrical device to activate a displaying cell. To display an image precisely, several millions of identical transistors are patterned on a wide glass panel. Since a minute damage on the pattern can causes a serious defect to display, it is important to inspect the pattern precisely. Taking the advantage of the fact that the pattern of good cell should be identical to that of adjacent cells, it would be a convenient way to compare a cell with its neighbor cells to find a defect. In practical applications, if the period of repetition could be represented as an integer number of digitized image pixel, it would be possible to find a damaged pixel readily. However, the period of pattern depends on the product size and cannot be determined as an integer always. In this paper, so called, pseudo-matching magnification algorithm has been introduced to solve the problem. A digital image was magnified and period of pattern can be determined as an integer from the processed image. It has been shown that the defects could be enhanced after the preprocessing of digital image. As a result, a TFT-pattern inspection system has been developed and it has been shown the proposed method is compatible for the inspection of repeated pattern.
Lead Frame is a core part of semiconductor IC and is used as a conductor to transmit electrical signal. In this study, an inspection system was developed that has utilized linear cameras and a method has been proposed for an automated inspection of LF. Mathematical morphology has been employed for the inspection. A modified thinning algorithm was proposed and has been used to make a master pattern of LF. The proposed method follows three steps to evaluate the quality of product. It is the first step to place the master on an object image precisely. Those have abnormal gray values in the object, are extracted as defective candidates. The last work is to evaluate the candidates according to a heuristic rule of decision. The proposed method has shown a good efficiency for the inspection of LF> It has been possible to find defect in a fast way and given minimal misjudgement. The proposed method is also efficient in inspecting etched products e.g. PCB and tape μBGA.