• 한국생산제조학회지
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• 제22권1호
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• pp.150-155
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• 2013

This work present a new method of sealing inspection system for vehicle in which foam rubber materials are used for sealing the vehicle parts. This system is composed from a devices comprising non-contact and real-time scanning on visual inspection in machine parts. We have been investigated qualitative factors that influenced on sealing system of vehicle structure which flexibly attenuated vibration and plenty of foam rubber materials having elastic property. However, there are different factors which still depended on outdated technique (personnel subjective judgment) in the performance inspection of rubber parts, specially for cross section inspection. Through a newly developed inspection system which recently applied for the production line, we successfully achieved more effective results of matching rate by about 80 % in the sealing performance inspection with 0.7% to 1.4% in the repeated errors. These are resulted from non-contacted response by CCD camera and vision program using geometry matching method. We expect that this system may be widely applied in the strict inspection parts of more diverse cross-section in future.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.7-13
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• 2021

Machine vision is a technology that helps the computer as if a person recognizes and determines things. In recent years, as advanced technologies such as optical systems, artificial intelligence and big data advanced in conventional machine vision system became more accurate quality inspection and it increases the manufacturing efficiency. In machine vision systems using deep learning, the image quality of the input image is very important. However, most images obtained in the industrial field for quality inspection typically contain noise. This noise is a major factor in the performance of the machine vision system. Therefore, in order to improve the performance of the machine vision system, it is necessary to eliminate the noise of the image. There are lots of research being done to remove noise from the image. In this paper, we propose an autoencoder based machine vision system to eliminate noise in the image. Through experiment proposed model showed better performance compared to the basic autoencoder model in denoising and image reconstruction capability for MNIST and fashion MNIST data sets.

• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.14-18
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• 2021

Electric Vehicle industry requires high technologies to stabilize apparatuses for the Coolant heater manufacturing. Vibrations of Leak Machine are one of the most critical factors for causing delivered of the defective product or poor inspection, which are the main reasons of the defects. In this study, the structure of the Leak Machine was analyzed through the experiment and the computer simulation to investigate the main reasons of the vibrations, and further to alter the design for the improved stability. And that design alterations were applied to the machine to identify the effects of those alterations. The result of the study shows that design alterations of the Leak Machine can effectively suppress about 97.8% of the vibrations, and further can improving the Inspection precision of the Coolant heater.

• 실천공학교육논문지
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• 제6권1호
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• pp.37-42
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• 2014

자동 시각 검사 장비는 전 세계적으로 제조업 기반의 기업들의 공장 자동화 시스템의 주요 장비로 자리 잡고 있다. 반도체, LCD, 철강, 제지 등 다양한 분야에서 품질관리의 자동화를 위하여 필수적으로 활용되고 있다. 그러나 대학, 직업전문학교 등의 교육기관에서는 이에 대한 교육이 거의 이뤄지지 못하고 있다. 본 논문에서는 자동 시각 검사 시스템의 기술훈련을 위하여 라인스캔 카메라 기반의 자동 시각 검사 장비 교육을 위한 실습 장비에 대해서 다루고 있다. 제작된 시스템은 산업현장에 널리 사용되고 있는 X-Y stage 기반으로 구성되었으며, 영상의 픽셀해상도는 $10-30{\mu}m$의 범위에서 가변적으로 조절 가능하다. 또한 조명구조에 따른 영상효과를 확인하기 위하여, 측면 직사조명과 동축조명을 장착하여 활용할 수 있도록 구성되어 있다. 이는 훈련자가 실습환경에서 다양한 조건들을 변경시키며 실습을 수행할 수 있음을 의미하며, 실제 제조 현장에서 활용되는 라인스캔 카메라 기반의 머신비전 시스템과 거의 동일한 기능을 수행하도록 제작되었다.

• 한국산학기술학회논문지
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• 제14권6호
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• pp.2624-2630
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• 2013

LED 칩 패키징에서 다이 본딩은 분할된 칩을 리드 프레임에 고정시켜 칩이 이후 공정을 견딜 수 있도록 충분한 강도를 제공하는 중요한 공정이다. 다이본딩 공정 중에서, 측정 단계는 정확한 에폭시 토출 위치 지정과 충분한 강도를 가지고 접합할 수 있도록 다이가 정확한 위치에 놓여있는지 상태를 결정하는데 있어 매우 중요하다. 본 연구에서는 LED 다이 본딩을 위한 머신 비전 기반의 측정 시스템을 개발하였다. 제안된 시스템에서 에폭시 토출과 어태칭 상태 검출을 위해 각각 2개의 카메라를 사용하였다. 제안된 측정 시스템에 새로운 비전 알고리즘을 적용하였고, 실험을 통해 본 알고리즘의 효율을 검증하였다. 비전 알고리즘을 이용하여 측정된 위치 오차는 $X:-29{\mu}m$, $Y:-32{\mu}m$, 회전오차는 3도 이내 인 것을 확인할 수 있었다. 결론적으로 제안된 머신 비전 기반의 측정 시스템을 통해 개발된 다이 본딩 시스템의 향상된 성능을 확인하였다.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1089-1095
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• 2010

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1235-1238
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• 2003

A rule-based CAPP(computer aided process planning) system is proposed in this research to develop integrated manufacturing process of machining and inspection using OMM(On-Machine Measurement) device. Generally workpiece composed of many primitive form features. This features are determined optimum inspection sequence by analyzing the feature information such as features-relationship, probe approach direction and etc. Proposed paper is more efficient method of CAIP(computer aided inspection planning) considered machining process

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1109-1114
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• 2015

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

• 한국정밀공학회지
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• 제14권11호
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• pp.84-92
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• 1997

The purpose of this study is to develop a geometric error model and path compensation algorithm for rotating axes of the 5-axis machine tools, by a method to calibrate a rotary table using one master ball and three LVDTs. It was developed a new methodology to measure 3 translation errors of the rotary table and with a compensation procedure for setup errors of the master ball. The method is experimentally verified using a ball-table and on-machine inspection method. The results showed that the geometric error models with the path compensation strategy can be practically used as a means for improving the accuracy of the machine tools with rotary table.

• 한국전기전자재료학회논문지
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• 제34권5호
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• pp.371-381
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• 2021

A machine vision inspection system consists of a camera, optics, illumination, and image acquisition system. Especially a scanning system has to be made to measure a large inspection area. Therefore, a machine vision line scan camera needs a line scan light source. A line scan light source should have a high light intensity and a uniform intensity distribution. In this paper, an offset calibration and slope calibration methods are introduced to obtain a uniform light intensity profile. Offset calibration method is to remove the deviation of light intensity among channels through adding intensity difference. Slope calibration is to remove variation of light intensity slope according to the control step among channels through multiplying slope difference. We can obtain an improved light intensity profile through applying offset and slope calibration simultaneously. The proposed method can help to obtain clearer image with a high precision in a machine vision inspection system.