• Current Optics and Photonics
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• v.2 no.1
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.392-398
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• 2013

As the essential techniques for the CD (Critical Dimension) measurement of the LCD pattern, there are various modules such as an optics design, auto-focus [1-4], and precise edge detection. Since the operation of image enhancement to improve the CD measurement repeatability, a ring type of the reflected lighting optics is devised. It has a simpler structure than the transmission light optics, but it delivers the same output. The edge detection is the most essential function of the CD measurements. The CD measurement is a vital inspection for LCDs [5-6] and semiconductors [7-8] to improve the production yield rate, there are numbers of techniques to measure the CD. So in this study, a new subpixel algorithm is developed through facet modeling, which complements the previous sub-pixel edge detection algorithm. Currently this CD measurement system is being used in LCD manufacturing systems for repeatability of less than 30 nm.

• Current Optics and Photonics
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• v.2 no.2
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• pp.153-164
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• 2018

In semiconductor manufacturing, critical dimensions indicate the features of patterns formed by the semiconductor process. The purpose of measuring critical dimensions is to confirm whether patterns are made as intended. The deposition process for an organic light emitting diode (OLED) forms a luminous organic layer on the thin-film transistor electrode. The position of this organic layer greatly affects the luminescent performance of an OLED. Thus, a system for measuring the position of the organic layer from outside of the vacuum chamber in real-time is desired for monitoring the deposition process. Typically, imaging from large stand-off distances results in low spatial resolution because of diffraction blur, and it is difficult to attain an adequate industrial-level measurement. The proposed method offers a new superresolution single-image using a conversion formula between two different optical systems obtained by a deep learning technique. This formula converts an image measured at long distance and with low-resolution optics into one image as if it were measured with high-resolution optics. The performance of this method is evaluated with various samples in terms of spatial resolution and measurement performance.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.531-537
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• 2014

Through-silicon vias (TSVs) are fine, deep holes fabricated for connecting vertically stacked wafers during three-dimensional packaging of semiconductors. Measurement of the TSV geometry is very important because TSVs that are not manufactured as designed can cause many problems, and measuring the critical dimension (CD) of TSVs becomes more and more important, along with depth measurement. Applying white-light scanning interferometry to TSV measurement, especially the bottom CD measurement, is difficult due to the attenuation of light around the edge of the bottom of the hole when using a low numerical aperture. In this paper we propose and demonstrate four bottom CD measurement methods for TSVs: the cross section method, profile analysis method, tomographic image analysis method, and the two-dimensional Gaussian fitting method. To verify and demonstrate these methods, a practical TSV sample with a high aspect ratio of 11.2 is prepared and tested. The results from the proposed measurement methods using white-light scanning interferometry are compared to results from scanning electron microscope (SEM) measurements. The accuracy is highest for the cross section method, with an error of 3.5%, while a relative repeatability of 3.2% is achieved by the two-dimensional Gaussian fitting method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1731-1739
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• 1993

An application of Scanning Tunneling Microscopy(STM) is investigated for the measurement of 3-dimensional profiles of the macro-machined patterns of which critical dimensions lie in the range of submicrometers. Special emphasis of this investigation is given to extending the measuring ranges of STM upto the order of several micrometers while maintaining superb nanometer measuring resolution. This is accomplished by correcting hysteresis effects of piezoelectric actuators by using non-linear compensation models. Detailed aspects of design and control of a prototype measurement system are described with some actual measuring examples in which fine It patterns can successfully be traced with a resolution of 1 nanometer over a surface range of $4{\times}2$ micrometers.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.11a
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• pp.431-443
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• 2004

Many e-Learning companies are incorporated for the last five years, but most of them are failed or merged by the other company. The main reasons are the absence of competitive strategies and recognition of critical success factors. There are many researches on the critical success factors of Information System (IS) and Electronic Commerce (EC) . We derived e-Learning success factors from the previous IS and EC researches. We classified the success factors into five dimensions, (1) contents management, (2) learner management, (3) business strategy, (4) organizational support and ability, (5) learning management system (LMS), and each dimension has 9 or more success factors measurement items. We surveyed the perceived importance of the success factors from the manager of South Korea e-Learning firms. The paper categorized the items into two or more factors for each dimension by the exploratory factor analysis. Finally, we conducted one-way ANOVA for each success factors by the business model. As a result, there is different importance level for each success factors by the business model. We concluded that each e-Learning company needs different strategies to their business model.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.108-113
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• 2022

The deep-learning-based measurement method with the through-focus scanning optical microscopy (TSOM) estimated the size of the object using the classification. However, the measurement performance of the method depends on the number of subdivided classes, and it is practically difficult to prepare data at regular intervals for training each class. We propose an approach to measure the size of an object in the TSOM image using the deep-learning regression model instead of using classification. We attempted our proposed method to estimate the top critical dimension (TCD) of through silicon via (TSV) holes with 2461 TSOM images and the results were compared with the existing method. As a result of our experiment, the average measurement error of our method was within 30 nm (1σ) which is 1/13.5 of the sampling distance of the applied microscope. Measurement errors decreased by 31% compared to the classification result. This result proves that the proposed method is more effective and practical than the classification method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.3
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• pp.315-325
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• 2017

The design dimension may not be satisfactory at the final stage due to the welding during the assembly stage, leading to cutting or adding the components in large structure constructions. The productivity is depend on accuracy of the welding quality especially at assembly stage. Therefore, it is of utmost importance to decide the component dimension during each assembly stage considering the above situations during the designing stage by exactly predicting welding deformation before the welding is done. Further, if the system that predicts whether welding deformation is equipped, it is possible to take measures to reduce deformation through FE analysis, helping in saving time for correcting work by arresting the parts which are prone to having welding deformation. For the FE analysis to predict the deformation of a large steel structure, calculation time, modeling, constraints in each assembly stage and critical welding length have to be considered. In case of fillet welding deformation, around 300 mm is sufficient as a critical welding length of the specimen as proposed by the existing researches. However, the critical length in case of butt welding is around 1000 mm, which is far longer than that suggested in the existing researches. For the external constraint, which occurs as the geometry of structure is changed according to the assembly stage, constraint factor is drawn from the elastic FE analysis and test results, and the magnitude of equivalent force according to constraint is decided. The comparison study for the elastic FE analysis result and measurement for the large steel structure based on the above results reveals that the analysis results are in the range of 80-118% against measurement values, both matching each other well. Further, the deformation of fillet welding in the main plate among the total block occupies 66-89%, making welding deformation in the main plate far larger than the welding deformation in the longitudinal and transverse girders.

• Korean Journal of Optics and Photonics
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• v.32 no.4
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• pp.172-179
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• 2021

A near-normal-incidence ellipsometer (NNIE) is suggested as an optical critical dimension (OCD) measurement system that is highly sensitive to the bottom defect of a sample with high-aspect-ratio structured patterns. Incident light passes through a polarizer and a phase retarder in sequence, and the reflected light from the sample also passes through them, but in reverse order. The operating principle of this NNIE, where a single polarizer and a single phase retarder are shared by the incident and reflected light, is studied, and a method to determine the ellipsometric constants from the measured intensities at proper combinations of the azimuthal angles of polarizer and retarder is presented.

• Journal of the Semiconductor & Display Technology
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• v.8 no.4
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• pp.7-13
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• 2009

The slender device(long length and thin width) manufactured by stereolithography process suffers from large curl distortion. This paper adapts two control parameters such as a critical exposure and a penetration depth. The measurement of the test parts dimension are carried out by reverse engineering method with the optical 3-dimensional measurement equipment. We investigate how each parameter contributes to the part accuracy and estimates the optimal set of parameters which minimizes the dimensional error of the test parts. Finally, As being an the RAM slot as being an example of the slender device, the RAM slot is made with the optimal values of control parameter and the results are investigated