Earticle

The ACF(Anisotropic Conductive Film) is used for bonding Drive IC and OLED display device panel. If ACF bonding process is problem, a malfunction of line defect can occur. Because electric resistance increase between the panel and drive IC after a period of time, drive IC can not supply enough current to the panel. This paper is studied on a method of test for line defect.

We propose a highly birefringent and dispersion compensating photonic crystal fiber based on a double line defect core. Using a finite element method (FEM) with a perfectly matched layer (PML), it is demonstrated that it is possible to obtain broadband large negative dispersion of about -400 to -427 ps/(nm.km) covering all optical communication bands (from O to U band) and to achieve the dispersion coefficient of -425 ps/(nm.km) at 1.55μm. In addition, the highest birefringence of the proposed PCF at 1.55 μm is 1.92 × 10^-2 and the value of birefringence from the wavelength of 1.26 to 1.8 μm (covering O to U bands) is about 1.8 × 10^-2 to 1.92 × 10^-2. It is confirmed that from the simulation results, the confinement loss of the proposed PCF is always less than 10^-3 dB/km at 1.55 μm with seven fiber rings of air holes in the cladding.

An automated circuit repair system was developed for enhancing the yield of nondefective liquid crystal panels, focusing on the resist patterns on the circuit material layer of thin-film transistor (TFT) substrates prior to etching. The developed system has an advantage over the parallel conventional system: In the former, the repair conditions depend on the type of resist whereas in the latter, the repair parameters must be fine-tuned for each circuit material. The developed system consists of a resist pattern defect inspection system and a pattern repair system for short and open defects. The repair system performs fine corrections of abnormal areas of the resist pattern. The open-repair system is equipped with a syringe to dispense resist. To maintain a stable resist diameter, a thermal insulator was installed in the syringe system. As a result, the diameter of the dispensed resist became much more stable than when no thermal insulator was used. The resist diameter was kept within the target of $400{\pm}100{\mu}m$. Furthermore, a prototype system was constructed, and using a dummy pattern, it was confirmed that the system worked automatically and correctly.

We have developed an automated circuit defect repair method. We focused on the resist patterns on the circuit material layer of TFT substrates before the etching process. In this paper, we report on the repair method that utilizes the syringe system and the stability of the open defect repair process.

We have developed an automated circuit defect inspection and repair method that can be used to improve the yield ratio of TFT-LCD. The method focuses on correcting resist patterns after the development process to ensure shape regularity. We built a prototype system and confirmed that the method is valid.

A quick and automatic detection with no harm to the goods is very important task for improving quality control, process control and labour reduction. In real fields of industry, defect detection is mostly accomplished by skillful workers. A narrow band eliminating spatial filter having characteristics of removing the specified spatial frequency is developed by the author, and it is proved that the filter has an excellent ability for on-line and real time detection of surface defect. By the way,. this spatial filter shows a ripple phenominum in filtering characteristics. So, it is necessary to remove the ripple component for the improvement of filter gain, moreover efficiency of defect detection. The spatial filtering method has a remarkable feature which means that it is able to set up weighting function for its own sake, and which can to obtain the best signal relating to the purpose of the measurement. Hence, having an eye on such feature, theoretical analysis is carried out at first for optimal design of narrow band eliminating spatial filter, and secondly, on the basis of above results spatial filter is manufactured, and finally advanced effectiveness of spatial filter is evaluated experimentally.

부식결함은 가스배관의 신뢰성평가 및 정비계획에 유의한 영향을 미친다. 부식결함은 정기적인 ILI를 통해 수집할 수 있지만 ILI 데이터의 효과적인 분석은 아직 미흡한 실정이다. 본 논문은 부식결함이 존재할 때 가스배관의 잔여수명을 예측하는 문제를 다룬다. 실제 운용 환경에서 배관 파라미터는 불확실성의 영향 하에 놓이게 되므로 확률적인 접근방법을 채택한다. 배관의 고장은 그 운용압력이 배관파열압력보다 클 때 발생하는 것으로 볼 수 있다. 따라서 배관의 고장확률은 운용압력이 배관파열압력보다 클 확률로서 정의된다. 이를 계산하기 위해 본 논문에서는 구조공학 분야에서 널리 쓰이는 First Order Reliability Method (FORM) 알고리즘을 이용한다. 배관파열압력을 얻기 위한 모델은 잘 알려진 Battelle 코드를 채택한다. ILI 데이터가 주어질 때 고장확률을 계산하는 과정은 Matlab GUI를 통해 제시하고 특히 부식결함의 클러스터링이 계산결과에 미치는 영향을 논의한다. 본 논문의 결과는 고장확률 추정의 정밀도를 높이고 효율적인 정비정책을 수립하는데 적절한 클러스터링이 필요함을 시사한다.

Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

부분방전 검출을 이용한 XLPE 케이블 진단은 중간 및 종단 접속재의 계면에 존재하는 결합을 검출할 수 있는 가장 효과적인 방법으로 제시되고 있지만 현장의 큰 노이즈로 인하여 신뢰성 있는 진단이 쉽지 않다. 하지만 국내에서 많은 연구가 이루어진 송전케이블 진단 기술을 바탕으로 배전케이블 진단에 적용하여 종단접속부에서 발생된 부분방전을 성공적으로 검출하였고 해체 조사를 통하여 결함을 검출하였다. 본 논문은 참고문헌[1]에 발표한 논문에 연결되는 논문으로 전편은 2004년 2월 부분방전 검출사례를 보고한 논문이고 본 논문에서는 8월 계획정전을 통하여 문제된 접속함을 교체한 후 해체조사를 통하여 결함을 검출한 사례보고이다.

2차전지산업은 수년간 빠르게 성장하였으나 최근 수요 둔화와 글로벌 공급사들의 공격적 투자로 어느 때보다 치열한 시장경쟁이 예고된다. 따라서 제조설비의 생산성을 높여 원가경쟁력을 높이기 위한 노력이 어느 때보다 중요해지고 있다. 2차전지 제조설비에서 병목인 전극공정은 다수의 제품을 한 설비에서 생산하는 반면 한 제품에서 다른 제품으로 교체하는데 긴 준비시간이 필요하다. 따라서 생산로트의 크기를 얼마로 하느냐는 설비 운영의 중요한 의사결정 요인이 되고 있다. 준비교체 손실 관점에서는 생산로트의 크기가 클수록 유리하지만 큰 생산로트는 제조설비의 재공을 증가시키고 이는 다시 전극공정에서 발생한 불량이 이후 조립공정 검사를 통해 발견되는데 걸리는 시간을 증가시켜 불량률을 증가시키는 문제를 초래한다. 본 연구에서는 이 문제에 대하여 대기행렬이론을 활용한 분석모형을 제공함으로써 제조설비의 운영 효율을 높이는 데 도움을 주고자 한다. 분석모형은 생산로트의 크기에 따라 전극공정의 준비교체로 인한 손실과 불량 로트 발생으로 인한 손실에 대하여 근사치를 계산하는 데 초점을 두고 있다. 이를 위하여 GI/G/c 대기행렬모형을 바탕으로 생산로트의 크기에 따라 불량 발생 메카니즘을 계산하는 분석모형을 제안하였다. 이 분석모형의 유용성을 입증하기 위하여 2차전지 제조기업에서 수집한 자료를 바탕으로 수리적 분석을 진행하였다. 이 결과 본 연구에서 제안하는 분석모형을 통해 생산로트의 크기에 따른 수율, 총생산량, 불량률의 변화를 분석할 수 있어 의사결정에 활용될 수 있을 것으로 기대된다.

The EV battery industry has grown rapidly over the years, and with the recent slowdown in demand and aggressive investment from global suppliers, fierce market competition is expected, requiring efficient operation of manufacturing lines more than ever. The electrode process, which is a bottleneck process in the EV battery manufacturing line, produces multiple products on a unit line, but switching from one product to another requires a long setup time. Therefore, the size of the production lot is an important decision-making factor in line operation. The larger the production lot size, there is a less setup loss, but a large production lot increases the WIP between electrode line and the subsequent assembly line, which increases the time to detect a defect occurred in the electrode process to be discovered after inspection in the assembly line. This study aims to help increase the operational efficiency of the EV manufacturing line by providing an analytic model using queuing theory. The analysis model focuses on approximating the loss due to setup of the electrode manufacturing line and the loss due to the occurrence of defective parts depending on the size of the production lot. To this end, based on the GI/G/c queuing model, a stochastic model is proposed to explain the defect occurrence mechanism depending on the size of the production lot. This study conducts an numerical analysis based on data collected from an actual EV battery manufacturing line to illustrate the usefulness of this model. As a result, it was found that the stochastic model proposed in this study can be used for decision making by analyzing yield, total production volume, defect rate according to the size of the production lot.