• IE interfaces
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• v.21 no.2
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• pp.151-160
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• 2008

Defect size distribution is a probability density function for the defects that occur on wafers or glasses during semiconductor/LCD fabrication. It is one of the most important information to estimate manufacturing yield using well-known statistical estimation methods. The defects are detected by automatic optical inspection (AOI) facilities. However, the data that is provided from AOI is not accurate due to resolution of AOI and its defect detection mechanism. It causes distortion of defect size distribution and results in wrong estimation of the manufacturing yield. In this paper, I suggest a size conversion method and a maximum likelihood estimator to overcome the vague defect size information of AOI. The methods are verified by the Monte Carlo simulation that is constructed as similar as real situation.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1519-1527
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• 2015

TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

• Proceedings of the Optical Society of Korea Conference
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• 2005.07a
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• pp.206-207
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• 2005

The gradient of the residual stress distribution in the mechanical defect on the optical fiber surface was investigated. This gradient of the residual stress distribution appeared in both of the core and the clad of the mechanical defect region on the optical fiber. The residual stress measurement was suggested as a investigation method of the mechanical defect on the optical fiber.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1115-1127
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• 2010

In order to increase the productivity in manufacturing TFT-LCD(thin film transistor-liquid crystal display), it is essential to classify defects that occur during the production and make an appropriate decision on whether the product with defects is scrapped or not. The decision mainly depends on classifying the defects accurately. In this paper, we present an effective classification method for film defects acquired in the panel production line by analyzing the intensity distribution and shape feature of the defects. We first generate a binary image for each defect by separating defect regions from background (non-defect) regions. Then, we extract various features from the defect regions such as the linearity of the defect, the intensity distribution, and the shape characteristics considering intensity, and construct a referential image database that stores those feature values. Finally, we determine the type of a defect by matching a defect image with a referential image in the database through the matching cost function between the two images. To verify the effectiveness of our method, we conducted a classification experiment using defect images acquired from real TFT-LCD production lines. Experimental results show that our method has achieved highly effective classification enough to be used in the production line.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.597-608
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• 2020

Purpose: The purpose of this paper is to present a probability distribution of the burst pressure of API 5L X65 pipes for the reliability assessment of corroded gas pipelines. Methods: Corrosion is a major cause of weakening the residual strength of the pipe. The mean residual strength on the corrosion defect can be obtained using the burst pressure code. However, in order to obtain the pipe reliability, a probability distribution of the burst pressure should be provided. This study is concerned with estimating the burst pressure distribution using Monte Carlo simulation. A response surface method is employed to represent the distribution parameter as a model of the corrosion defect size. Results: The experimental results suggest that the normal or Weibull distribution should be suitable as the probability distribution of the burst pressure. In particular, it was shown that the probability distribution parameters can be well predicted by using the depth and length of the corrosion defect. Conclusion: Given a corrosion defect on the pipe, its corresponding burst pressure distribution can be provided at instant. Subsequently, a reliability assessment of the pipe is conducted as well.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.120-125
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• 2007

Put Abstract text here The strain distribution measurement for wall thinned pipe bends by ESPI is presented. Defect types observed in the steel piping in the nuclear power plants (NPP) are the crack at the weld part and the wall thinning defect in the pipe bends. Especially, the wall thinning defects in the pipe bends due to the flow-accelerated corrosion (FAC) is a main type of defects observed in the carbon steel piping system. ESPI is one of the optical non-destructive testing methods and can measure the stress and the strain distribution of the object subjected by the tensile loading or the internal pressure. In this paper, the strain distribution of the wall thinned pipe bends due to the internal pressure will be measured by ESPI technique and the results are discussed. From the results, the size of the wall thinning defect can also be measured approximately.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1413-1416
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• 2005

An infrared temperature sensor module developed for the detection of defects in a plate was modified to use in a cylinder. A set of optical fiber leads and a mechanism maintaining sensor-object distance constant were utilized for the modification of the IR sensor module. The detection performance was experimentally investigated, and the measured temperature was also compared with computed temperature distribution. The experimental outcome indicates that the detection of a simulated defect is readily available. The temperature distribution is better for defect detection than that with the previous device. In addition, the measured distribution is comparable to the calculated one using a heat conduction equation. The developed device of defect detection is suitable to be utilized in chemical processes where most of vessels and piping systems are in the shape of a cylinder.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.339-348
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• 2021

In recent software defect prediction research, defect prediction between cross projects and cross-version projects are actively studied. Cross-version defect prediction studies assume WP(Within-Project) so far. However, in the CV(Cross-Version) environment, the previous work does not consider the distribution difference between project versions is important. In this study, we propose an automated Bayesian optimization framework that considers distribution differences between different versions. Through this, it automatically selects whether to perform transfer learning according to the difference in distribution. This framework is a technique that optimizes the distribution difference between versions, transfer learning, and hyper-parameters of the classifier. We confirmed that the method of automatically selecting whether to perform transfer learning based on the distribution difference is effective through experiments. Moreover, we can see that using our optimization framework is effective in improving performance and, as a result, can reduce software inspection effort. This is expected to support practical quality assurance activities for new version projects in a cross-version project environment.

• Electrical & Electronic Materials
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• v.10 no.9
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• pp.881-888
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• 1997

This study demonstrats the profiles of phosphorus ions in silicon by MeV implantation(1∼3 MeV). Implanted profiles could be measured by SIMS(Cameca 4f) and compared with simulation results(TRIM program and analytical description method only using on Pearson function). The experimental result in the peak concentration region has a little bit deviation from simulation data. By RBS and Channeling measurements the defect distribution of implanted samples could be measured and spectrum are calibrated depth with RUMP simulation By XTEM measurement the thickness of defect zone also could be measured. Finally thermal annealing for the electrical activation of implanted ions carried out by RTA(rapid thermal annealing). The concentration-depth profiles after heat treatment was measured by SR(spreading resistance)-method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.504-508
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• 2022

Single crystal gallium oxide (Ga₂O₃) has been an emerging material for power semiconductor applications. However, the defect distribution of Ga₂O₃ substrates needs to be carefully characterized to improve crystal quality during crystal growth. We analyzed the type and the distribution of defects on commercial (-201) Ga₂O₃ substrates to get a basic standard prior to growing Ga₂O₃ crystals. Etch pit technique was employed to expose the type of defects on the Ga₂O₃ substrates. Synchrotron white beam X-ray topography was also utilized to observe the defect distribution by a nondestructive manner. We expect that the observation of defect distribution with three-dimensional geometry will also be useful for other crystal planes of Ga₂O₃ single crystals.