• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.383-386
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• 2002

It is very important to inspect color of printed texture in the textile process. To distinguish the color of the printed texture, RGB color values obtained from a scanner must be transformed to the standard colorimetric system used in the textile industry. It is XYZ color system that is defined by CIE(Commission Internationale do 1Eclairage). The mapping from RGB to XYZ color values is not simple and the scanner has even a positional deviation of RGB colors. In this paper an automatic color inspection method using a general scanning machine is presented. We used a U(neural network) model to map RGB to XYZ and compensate the positional error. In the real experiments, this inspection system shows to get very exact XYZ values from the traditional scanner regardless of the measuring position.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.25-30
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• 2019

In this paper, we have analyzed manufacturing problems of the scaffold with pores using FDM 3D printer and PLGA. We suggested the solutions using 3SC practical TRIZ. We selected the final solution used machine learning. We reduced number of experiments using most influential factor after analysis print factors. We printed the scaffold and measured pore size. We created the regression model using python tensorflow. The print condition data of measured pore size was used as training data. We predicted the pore size of printed condition using regression model. We printed the scaffold using the predicted the print condition data. We quantitatively compare the predicted scaffold pore size data and the measured scaffold pore size data. We got satisfactory result.

• 한국기계가공학회지
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• 제12권5호
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• pp.9-15
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• 2013

Roll-to-roll printing technology has lately become a subject of special interests in the field of printed electronics. Since this technology has the advantage that continuous and mass production is possible. And for high precision register control is required in multi-layer printing to produce the electronic devices, this is one of the most important technologies in roll-to-roll printing technology. Register error could be generated by various reasons like eccentricity of roll and thermal deformation due to temperature variation in drying section. In this study, the effect of tension variation on the register was analyzed. The results of these analyses show that it is essential to consider the tension disturbance which is generated by the change of temperature in drying section, and conventional register model has limitation to estimate the register error. In order to overcome the limitation of the register model, advanced register model based on the SI process was developed. Also, the performance of the developed model was verified experimentally.

• 대한치과기공학회지
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• 제38권3호
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• pp.185-191
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• 2016

Purpose: The purpose of this study were to evaluate the quality of dental prostheses printed by 3-dimensional printing system. Methods: Mater model was prepared and ten study models were fabricated. Ten single crowns were printed by 3D-printing system(Resin group) and another ten single crowns using casting method were manufactured(Metal group). The marginal adaptation of single crowns were measured using by silicone replica technique. Silicone replicas were sectioned four times. The marginal adaptations were evaluated using by digital microscope. Statistical analyses were performed with Mann-Whitney test(${\alpha}=0.05$). Results: $Mean{\pm}standard$ deviations of all marginal adaptations were $92.1(20.0){\mu}m$ for Metal group and $69.7(12.3){\mu}m$ for Resin group. Two groups were no statistically significant differences(p>0.05). Conclusion: Marginal adaptation of single crowns printed by 3D-printing system were ranged within the clinical recommendation.

• Journal of Korean Neurosurgical Society
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• 제65권4호
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• pp.489-498
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• 2022

Spatial insight into intracranial pathology and structure is important for neurosurgeons to perform safe and successful surgeries. Three-dimensional (3D) printing technology in the medical field has made it possible to produce intuitive models that can help with spatial perception. Recent advances in 3D-printed disease models have removed barriers to entering the clinical field and medical market, such as precision and texture reality, speed of production, and cost. The 3D-printed disease model is now ready to be actively applied to daily clinical practice in neurosurgical planning, simulation, and training. In this review, the development of 3D-printed neurosurgical disease models and their application are summarized and discussed.

• 한국CDE학회논문집
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• 제9권4호
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• pp.416-424
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• 2004

In this paper, the heat transfer analysis and thermal stress analysis of the PCB(Printed Circuit Board) equipped in electronic Packages are carried out for various may types of chips on the PCB. And two structural PCB models are used in the analyses. The electronic chips on the PCB usually emit heat and this heat generates the thermal stress around the chip. The thermal load due to the heat generation of chips on the PCB may cause the malfunction of the electronic packages such as a monitor. a computer etc. Hence, the PCB should be designed to withstand these thermal loads. In this paper, the heat transfer analysis and thermal stress analysis are executed for the PCB model with pins and the analysis results are compared with the results for the PCB model without pins. The analysis results show that the PCB model without pins is not good for the thermal stress analysis of PCB, even though these two models have similar heat transfer characteristics. The analysis results also show that the highest thermal stress occurs in the pin especially attached to the highest temperature chip, and the PCB constrained to the electronic package on the long side is structurally more stable than other cases. The analyses of the PCB are executed using the finite element analysis code, NISA.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.674-675
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• 2016

본 논문에서는 전기 및 전자 쓰레기의 대책으로 Printed Circuit Board (PCB) 부착형 Radio-Frequency Identification (RFID) 태그 칩을 이용한 사물인터넷 디바이스 생산 공정에 대한 모델을 제안한다. 전기 및 전자제품은 PCB 부품실장 공정과 검사가 필요하다. 또한 현재 제조사들이 사용하는 바코드 시스템은 Surface Mount Technology (SMT)공정이 완료되기 전까지 PCB 이력 관리가 불가능하다. 논문에서 제안한 PCB 부착형 RFID 태그 칩을 이용한 사물인터넷 디바이스 생산 공정 모델은 바코드 방식과 같은 출력-부착 단계가 필요하지 않다. 태그 칩은 각 단계의 공정 데이터가 기록될 수 있고, 데이터베이스 시스템 (DBMS) 접속 횟수를 현격히 줄일 수 있다.

• 융복합기술연구소 논문집
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• 제1권1호
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• pp.34-40
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• 2011

In this paper, a hybrid design tool combining one-dimensional(1D) lumped model and three-dimensional computational fluid dynamics(CFD) approach has been developed in order to evaluate the performance of inkjet print head and droplet control process are studied to reduce the deviations between nozzles which affect the size of the printed line for the industrial application of direct writing on printed circuit boards(PCB). 1D lumped model analysis shows that it is useful tool for evaluating performance of an inkjet head by varying the design parameters. The differences in ejected volume and droplet velocity between analytical and experimental result are within 12%. Time sequence of droplet generation is verified by the comparison between 3D analysis result and photographic images acquired by stroboscopic technique. In addition, by applying DPN process, velocity and volume uniformity between nozzles is dramatically improved that the tolerance achieved by the piezoelectric inkjet printhead across the 64 nozzles is 5 to 8%. A printed line pattern is successfully obtained using the fabricated inkjet print head and droplet calibration system.

• 한국멀티미디어학회논문지
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• 제24권3호
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• pp.382-395
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• 2021

In this study, character recognition using deep learning is performed among the various defects in the PCB, the purpose of which is to check whether the printed characters are printed correctly on top of components, or the incorrect parts are attached. Generally, character recognition may be perceived as not a difficult problem when considering MNIST, but the printed letters on the PCB component data are difficult to collect, and have very high redundancy. So if a deep learning model is trained with original data without any preprocessing, it can lead to over fitting problems. Therefore, this study aims to reduce the redundancy to the smallest dataset that can represent large amounts of data collected in limited production sites, and to create datasets through data enhancement to train a flexible deep learning model can be used in various production sites. Moreover, ResNet model verifies to determine which combination of datasets is the most effective. This study discusses how to reduce and augment data that is constantly occurring in real PCB production lines, and discusses how to select coresets to learn and apply deep learning models in real sites.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.463-465
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• 2021

현재 식품 포장 및 박스에 인쇄된 유통기한 검사 방법은 일부 제품만 샘플링하여 사람의 눈으로 검사하는 방법이다. 이러한 샘플링 검사는 극히 일부분의 제품만 검사 가능하다는 한계를 지니고 있다. 따라서 카메라를 활용한 정확한 검사가 요구된다. 본 논문에서는 제품 포장에 인쇄된 유통기한 결함 검출방법에 인공지능 기술인 딥 러닝 객체인식 기술 모델을 제안한다. 제안된 방법으로는 딥러닝 객체인식 모델 중에 Faster R-CNN 모델을 이용해 인쇄된 유통기한을 검출을 학습하고 Faster R-CNN 방법을 이용해서 수집된 칼라이미지를 그레이 이미지와 이진화 이미지로 변환한 이미지에 대해 각각 성능을 비교하고 검출 성능을 확인한다. 딥 러닝 기술에 적용한 박스에 인쇄된 유통기한 검출 성능은 기존 비전 검사기의 검출 성능과 비슷한 검출 성능을 보였다.