dc.description.abstract | In order to improve profits for TFT-LCD liquid crystal display manufacturers, other than producing high value-added products, firms can also reduce waste in the manufacturing process itself. This study focuses on the background of the glass cutting process, in order to explore the use of a machine vision in a cutter wheel after high osmotic pressure glass cutting that can replace the existing manual inspection methods. A reduction in waste can also be achieved by the implementation of an early warning system.
The pre-processing of the detection method includes edge detection, binarization, patterns filtering, and thinning, then the image is processed using horizontal projection to achieve a graph of the pixel cross-section of the glass. Afterwards, the truncated average end value determines whether the rib mark line is present. Two different detection methods, the Hough transformation and the least squares method, then measure the amount of straight-line distance of the rib mark line. There are advantages and disadvantages of different image detection methods when determining the correct rate, average execution speed, and measurement accuracy. The accuracy assessment experimental design was performed using the MAPE value, with Microsoft Visual C ++ 2010 running OpenCV. There were 95 flawless images and 130 flawed images taken of the experimental samples which had a glass thickness of 0.5mm. In total, 225 test sample images were taken, and through improved testing and detection methods, the flawed and flawless image correct image determination rate was 100%. The average execution speed was 0.094 seconds, with MAPE values of 5.93%. Finally, there were 30 flawless images and 30 flawed images taken of experimental samples which had a glass thickness of 0.7mm, and the flawed and flawless correct image determination was again 100% correct. The average execution speed the MAPE values of 0.7mm glass thickness samples were similar to the 0.5mm glass thickness experimental results. This method can be successfully applied to determine of different glass cross-sectional thicknesses. | en_US |