• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1812-1816
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• 2011

This research developed chemical flow control system(CFCS) essential for spinner equipment in nano semiconductor manufacturing process under the 100nm to prevent complex process defect due to missing spread after chemical injection. The devices developed in this research, which can be swiftly replaced in case abnormal state element changes or wafer manufacturing defect occurs, are anticipated to improve module yield as well as real-time monitoring on the state element. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, we can be exactly detected in five abnomal process type.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.76-83
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• 2023

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.471-477
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• 2021

In the field of display, a smart factory means more efficient display manufacturing using AI/BIG DATA technology not only for job automation, but also for existing process management, moving facilities, process abnormalities, and defect classification. In the past, when defects appeared in the display manufacturing process, the classification of defects and coping with process abnormalities were different, a lot of time was consumed for this. However, in the field of display manufacturing, advanced process equipment must be used, and it can be said that the competitiveness of the display manufacturing industry is to quickly identify the cause of defects and increase the yield. In this paper, we will summarize the cases in which smart factory AI/BIG DATA technology is applied to domestic display manufacturing, and analyze what advantages can be derived compared to existing methods. This information can be used as prior knowledge for improved smart factory development in the field of display manufacturing using AI/BIG DATA.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.18-23
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• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.

• Journal of Distribution Science
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• v.17 no.4
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• pp.51-57
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• 2019

Purpose - This study aims to improve the distribution structure of the OLED market and develop cost-effective optimization techniques. Specifically, it is a study on the optimization of ferric chloride to improve the etch of SUS MASK for OLED. Research design, data, and methodology - Applying the optimal conditions of the experiment, the final confirmation was evaluated for improvement by the Process Capability Index (Cpk). It is possible to derive social performance such as improvement of precision of SUS MASK manufacturing, economic performance such as defect rate, reduction of waste generation and treatment cost, technological achievement such as SUS MASK production technology, improvement of profit structure of technology development and process improvement do. Results - The improvement of the Cpk before the improvement was made was confirmed to be 0.57% with a defect estimate of 25.07% with a failure estimate of 0.57% after the improvement, and 8.84% with a failure estimate of 0.57% level after the improvement. Conclusions - If the conclusions obtained from the specimen experiment are applied to the manufacturing process of SUS MASK, it will be possible to expect excellent cost-effective competitiveness due to the improvement of precision and reduction of defect rate to enhance the OLED market penetration.

• Fire Science and Engineering
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• v.30 no.3
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• pp.94-103
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• 2016

This study analyzed the cause and liability of a car fire. The car was purchased 1 year ago and had traveled 8,500 km. When the car stopped at a red right and was about to start when the light turned green, the car next to it sounded itsa horn. As a result, the driver stopped the car and found that there was a fire in the engine compartment, which the fire brigade subsequently extinguished. This car fire may have been caused by an electrical spark from a screw hook inserted into the battery + terminal. Therefore, the courts decided that the car owner or driver was not responsible for the fire, because the electrical spark from the hook that caused it resulted from the automaker's manufacturing defect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1725-1728
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• 2009

This research developed process control device and FGV pattern generating device essential for full gate visual inspection to improve process so that defect detection capability may be maximized in specified environment. The devices developed in this research, which can be swiftly replaced in case loss or error occurs, are anticipated to improve module yield as well as maintain tact loss near '0'. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, detection rates were 98.1% and 99.1% respectively for pixel defect by tact and line defect, and yield of the entire module process including gate and visual level test increased up to 98.3%.

• Journal of Korean Society for Quality Management
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• v.20 no.2
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• pp.76-93
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• 1992

The purpose of this study, by surveying the status of firms, measurement-related investment and the defect rate, is to analyze the effect of measurement-related investment and to propose a scheme of efficient measurement-related investment which reduces the defect rate. For this project we obtain the data of the status of the measurement-related investment and the defect rate of 928 firms in Korean manufacturing industry by mailing survey. One of our results shows that the firms which have measurement standard laboratory, i.e, which invest in measurement-related area comparatively high, have the defect rate about 0.8% lower than those firms which don't have measurement standard laboratory. Also we find that the small-and-middle size firms have worse measurement-related facility than the large firms and the firms in the heavy-chemical industry have higher measurement-related investment effect than the firms in the light industry.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.222-228
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• 1999

The two-microphone sound-intensity technique has been used for the detection of defects in radially loaded ball bearings. The difference in the sound-intensity levels measured for bearings with no defect and for those with intentionally introduced defects of different sizes in their elements under various operating conditions of loads and speeds is demonstrated. A change in the intensity frequency spectrum because of the defects is observed. The results show that the detectability of an outer-race defect is much better than that of on inner-race or ball defect. It is difficult to detect defects at lower speeds. Sound-pressure measurements were also performed fur comparison, and it is shown that the detectability of defects by sound-intensity measurements is better than that by sound-pressure measurements.