• 소성∙가공
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• 제9권5호
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• pp.533-538
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• 2000

This study has been carried out to develop a CRT die using hot forging. The conventional CRT die made by casting has defects such as void and inclusion. These defects of the cast die make micro-spots on the surface of the CRT which affect the quality of the final product. So, a hot forging process is developed to avoid these defects of CRT die by the model material test and the rigid-plastic FEM. Firstly, model material tests are carried out with plasticine billets in order to investigate the material flow pattern in the die cavity and to get the reasonable initial values for designing the preform in the FE simulation. And then a finite element analysis has been performed to Predict the preform and the forging load of a CRT die. We also suggest an integrated die-set which combines two die-sets into one die-set to save manufacturing time and cost in case of similar die-size.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.175-179
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• 1998

The insulation of cable which used for Ultra-High Voltage(UHV) underground power transmission requires excellent insulation capability for high voltage. The typical insulation materials are used XLPE, EPR, etc, but insulation efficiency of these is affected by void or alien substances, existed at the inside of insulators. In this paper, the partial discharge patterns of the defects within insulation cable are observed and analyzed. In this test, void, fiber and metal inclusions which possibly exist in cables, are simulated and investigated the patterns of partial discharges for each models Also the relations between calculated field strength and the insulation breakdown voltage. The experiment shows distinct partial discharge patterns in accordance with the kinds of defects within Insulation cable.

• 한국군사과학기술학회지
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• 제13권1호
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• pp.77-83
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• 2010

In this paper, we proposed new outworn aircraft management procedure. ROKAF has both good management skill and information system, AMMIS, regarding aircraft maintenance based on all kinds of aircraft's defects. To optimize and secure aircraft's operation, management of the outworn aircraft is very important for ROKAF. With respect to these outworn aircraft's defects and maintenance, we analyzed defects occurrence pattern of outworn aircraft by using AMMIS data and Market Basket Analysis, and found the specified association rules for each defect. By using these association rules, we developed new management procedure for outworn aircraft based on the results of affinity analysis. The management procedure in this paper will also be used to optimal operation and maintenance of other aircraft and weapon systems.

• 반도체디스플레이기술학회지
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• 제10권1호
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4763-4775
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• 2020

This research aims to develop a deep learning-based method that automatically detects and segments the defects on railroad surfaces to reduce the cost of visual inspection of the railroad. We developed our segmentation model by modifying a fully convolutional network model [1], a well-known segmentation model used for machine learning, to detect and segment railroad surface defects. The data used in this research are images of the railroad surface with one or more defect regions. Railroad images were cropped to a suitable size, considering the long height and relatively narrow width of the images. They were also normalized based on the variance and mean of the data images. Using these images, the suggested model was trained to segment the defect regions. The proposed method showed promising results in the segmentation of defects. We consider that the proposed method can facilitate decision-making about railroad maintenance, and potentially be applied for other analyses.

• 한국기계가공학회지
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• 제14권1호
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• pp.15-20
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• 2015

I developed a high-quality metal door with a hologram-pattern design using a high-speed electroforming process. In this study, the major processes were master production, conducting grant, nickel-sulfamate acid electroforming, ablation treatment, and final dressing. The processing system was provided with a nickel sulfamate pole, and a rotary-pole PP-plating jig in a circular tank. This approach could reduce defects and errors, as much as possible, by its use of a hologram pattern to create the master of a metal door. The thin-sheet metal-creation process for the door built-in metal pattern using electroforming with hologram was successful.

• 한국건설관리학회논문집
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• 제16권2호
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• pp.21-28
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• 2015

공사비 증가와 공기 지연 등 건설프로젝트에 악영향을 미치는 건설품질결함은 지속적으로 발생하고 있다. 그간 결함을 유발시키는 원인들을 규명하기 위한 연구는 다수 있었으나, 원인들 간의 상관관계를 분석한 연구는 충분히 이루어지지 않았다. 본 논문에서는 국내 30개 프로젝트에서 발생한 1,241건의 부적합 사례 중 831건의 건축공종 부적합 사례를 토대로 건설품질결함의 발생요인을 발생단계, 발생현상, 기인원인, 처리방안으로 나누어 이들 간의 상관관계를 분석하고자 한다. 상관분석을 통해 부적합은 주로 조달 및 시공단계에서 기능결함 및 시공결함의 형태로 발생함을 알 수 있었다. 주로 작업자의 실수, 조악한 품질의 자재사용, 그리고 잘못된 시공방법에 의해 발생되는 품질결함은 주로 특채, 수리, 재작업의 방법으로 처리되어 공사비 증가 및 공기 지연을 가져옴을 알 수 있었다. 본 논문은 향후 품질결함의 발생과정을 규명하고 효율적인 품질결함 방지대책을 수립하는 데에 있어 중요한 이론적 배경과 정량적 지표를 제공했다는 데 그 의의가 있다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.1117-1120
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• 2001

Chemical mechanical planarization(CMP) has emerged as the planarization technique of choice in both front-end and back-end integrated circuit manufacturing. Conventional CMP process utilize a polyurethane polishing pad and liquid chemical slurry containing abrasive particles. There have been serious problems in CMP in terms of repeatability and defects in patterned wafers. Since IBM's official announcement on Copper Dual Damascene(Cu2D) technology, the semiconductor world has been engaged in a Cu2D race. Today, even after~3years of extensive R&D work, the End-of-Line(EOL) yields are still too low to allow the transition of technology to manufacturing. One of the reasons behind this is the myriad of defects associated with Cu technology. Especially, dishing and erosion defects increase the resistance because they decrease the interconnection section area, and ultimately reduce the lifetime of the semiconductor. Methods to reduce dishing & erosion have recently been interface hardness of the pad, optimization of the pattern structure as dummy patterns. Dishing & erosion are initially generated an uneven pressure distribution in the materials. These defects are accelerated by free abrasive and chemical etching. Therefore, it is known that dishing & erosion can be reduced by minimizing the abrasive concentration. Minimizing the abrasive concentration by using Ce$O_2$ is the best solution for reducing dishing & erosion and for removal rate. This paper introduce dishing & erosion generating mechanism and a method for developing a semi-rigid abrasive pad to minimize dishing & erosion during CMP.

• 비파괴검사학회지
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• 제25권2호
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• pp.81-86
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• 2005

본 논문에서는 반도체 패키지 내부결함의 비파괴 정량평가를 위한 ESPI 기법을 이용한 시스템 및 검사기 법을 제안하고 있으며, 검사시스템은 ESPI 검사장치, 열변형유도장치, 단열챔버로 구성되어있다. 기존 초음파, X-ray 기반의 검사기법에 비하여 측정시간 및 검사방법이 용이하며, 결함의 정량검출이 가능하다는 장점이 있다. 검사결과에서 대부분의 결함이 열 방출이 많은 칩 주위에서 박리결함으로 나타났으며, 원인은 층간 접착강도의 약화와 열분배 설계에서 문제점인 것으로 사료된다.

• 한국인터넷방송통신학회논문지
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• 제11권4호
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• pp.99-104
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• 2011

본 논문은 사출성형 제품에 존재하는 여러 가지의 패턴의 결함을 신경회로망을 이용하여 검출하는 방법을 제안하였다. 시스템의 성능을 향상시키기 위하여 룩업테이블을 이용하였고, 기존의 이미지 비교에 의한 방법을 지양하여 결함분류를 위한 신경회로망의 학습표본을 위한 특징점을 추출하고 결함추출과 분류알고리즘을 제안하였다. 총 500개의 사출성형 제품의 패턴에 대하여 신경회로망의 학습을 통하여 약 3%의 제품의 패턴에서 결함을 검출하였고 패턴의 직경에 대한 불량으로 대부분 분류되었다. 제안된 시스템을 이용한 결함 검출 방법은 사출성형 제품의 미세한 패턴을 검출하는 데 시간과 경비를 줄일 수 있는 효과적인 대안으로 기대한다.