• 제어로봇시스템학회논문지
• /
• 제14권5호
• /
• pp.444-452
• /
• 2008

This paper presents an overall image processing approach of defect inspection of patterned TFT-LCD panels for the real manufacturing process. A prototype of AOI(Automatic Optical Inspection) system which is composed of air floating stage and multi line scan cameras is developed. Adjacent pattern comparison algorithm is enhanced and used for pattern elimination to extract defects in the patterned image of TFT-LCD panels. New region merging algorithm which is based on border expansion is proposed to identify defects from the pattern eliminated defect image. Experimental results show that a developed AOI system has acceptable performance and the proposed algorithm reduces environmental effects and processing time effectively for applying to the real manufacturing process.

• 산업공학
• /
• 제21권2호
• /
• pp.151-160
• /
• 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.

• 광학세계
• /
• 통권154호
• /
• pp.46-56
• /
• 2014

• 한국지능시스템학회논문지
• /
• 제13권4호
• /
• pp.480-485
• /
• 2003

인쇄회로기판을 조립하는 SMT (surface mount technology) 라인의 AOI (automatic optical inspection) 형 검사기를 대상으로, 검사시간 단축을 위한 경로계획 방법을 제안한다. 기판에 존재하는 검사 윈도우들은 카메라의 FOV (field-of-view) 크기를 고려하여 클러스터링 되어야 하며, 전체 검사시간의 단축을 위하여 클러스터의 수를 최소화하는 것이 바람직하다. 주어진 기판에 대한 클러스터의 수를 최소화하기 위한 유전자 알고리즘을 새로이 제안하며, 이를 사용한 효과적 경로계획 방법을 제시한다. 상용 검사기를 대강으로 시뮬레이션을 수행하며, 비교 평가를 통하여 제안된 방법의 유용성을 검증한다.

• 제어로봇시스템학회논문지
• /
• 제21권8호
• /
• pp.788-793
• /
• 2015

This paper proposes a path planning algorithm to reduce the inspection time of AOI (Automatic Optical Inspection) machines for SMT (Surface Mount Technology) in-line system. Since the field-of-view of the camera attached at the machine is much less than the entire inspection region of board, the inspection region should be clustered to many groups. The image acquisition time depends on the number of groups, and camera moving time depends on the sequence of visiting the groups. The acquired image is processed while the camera moves to the next position, but it may be delayed if the group includes many components to be inspected. The inspection delay has influence on the overall job time of the machine. In this paper, we newly considers the inspection delay time for path planning of the inspection machine. The unified approach using genetic algorithm is applied to generates the groups and visiting sequence simultaneously. The chromosome, crossover operator, and mutation operator is proposed to develop the genetic algorithm. The experimental results are presented to verify the usefulness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.109.2-109
• /
• 2001

In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...

• 한국멀티미디어학회논문지
• /
• 제24권8호
• /
• pp.988-999
• /
• 2021

AOI (Automatic Optical Inspection) of PCB (Printed Circuit Board) is a very important step to guarantee the product performance. The process of registering components called teaching mode is first perform, and AOI is then carried out in a testing mode that checks defects, such as recognizing and comparing the component mounted on the PCB to the stored components. Since most of registration of the components on the PCB is done manually, it takes a lot of time and there are many problems caused by mistakes or misjudgement. In this paper, A components classifier is proposed using YOLO (You Only Look Once) v2's object detection model that can automatically register components in teaching modes to reduce dramatically time and mistakes. The network of YOLO is modified to classify small objects, and the number of anchor boxes was increased from 9 to 15 to classify various types and sizes. Experimental results show that the proposed method has a good performance with 99.86% accuracy.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 D
• /
• pp.2453-2455
• /
• 2003

We propose a path planning method to reduce the inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• 디지털융복합연구
• /
• 제13권1호
• /
• pp.269-274
• /
• 2015

IT 산업의 발달로 AOI 장비의 보급이 확산되고 있으며, 장비의 사용되는 카메라의 높은 해상도를 요구하고 있다. 높은 해상도를 얻기 위해 카메라의 중량이 증가되고 있으며, 그로 인해 진동변위가 커지게 되어 촬상에 문제가 생기고 제어 또한 어려워지고 있다. 본 연구에서는 유한요소 해석프로그램인 NX/NASTRAN을 이용하여 카메라가 관성에 의한 충격력을 받을 때의 과도응답분석을 해 보았다. 또한 Laser Interferometer 측정 결과와의 상관관계 분석을 통하여 향후 AOI의 구조 개선 시, 유한요소해석으로 설계의 신뢰성을 검증할 수 있도록 하기 위한 해석모델을 개발하였다.

• 제어로봇시스템학회논문지
• /
• 제16권7호
• /
• pp.695-702
• /
• 2010

This paper presents an image alignment algorithm for application of AOI (Automatic Optical Inspection) based on SIFT. Since the correspondences result using SIFT descriptor have many wrong points for aligning, this paper modified and classified those points by five measures called the CCFMR (Cascade Classifier for False Matching Reduction) After reduced the false matching, rotation and translation are estimated by point selection method. Experimental results show that the proposed method has fewer fail matching in comparison to commercial software MIL 8.0, and specially, less than twice with the well-controlled environment’s data sets (such as AOI system). The rotation and translation accuracy is robust than MIL in the noise data sets, but the errors are higher than in a rotation variation data sets although that also meaningful result in the practical system. In addition to, the computational time consumed by the proposed method is four times shorter than that by MIL which increases linearly according to noise.