• 한국산학기술학회논문지
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• 제15권5호
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• pp.2567-2572
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• 2014

본 연구개발은 PCB소자 분리에 있어 개별적 레이저 커팅의 문제점을 개선하는 것으로, 다수개의 PCB소자가 결합된 PCB시트를 단시간에 커팅 할 수 있는 멀티지그 개발이 목적이다. 설계는 베이스프레임에 PCB서포터가 안착, 모델별 PCB서포터가 분리가능하게 설계 하였으며, 상부 레이저 투과공의 고정을 위하여 네오디움 자석을 양쪽에 각각 채택 지그를 완료 하였다. 개발성과는 하나의 베이스프레임으로 다양한 규격의 PCB소자 및 모듈의 고정과, PCB소자에 연결된 브릿지의 컷팅작업이 가능하도록 설계, 프레임제작과 교체에 소요되는 시간과 비용을 줄여 생산원가의 절감형 지그 개발로, 기존 타발식에 비해 정밀도 약 70% 상향 및 시설 투자비 약 400%를 절감하였다.

• 한국산학기술학회논문지
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• 제15권8호
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• pp.4736-4741
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• 2014

본 연구는 PCB기판 세척에 관한 것으로 기존 세척 방법인 침전식 세척의 단점인 PCB기판 표면실링제와 접착제 공정에서 형성된 이물질이 달라붙거나 끼워 있는 경우, 쉽게 제거되지 못하는 문제점이 있었다. PCB기판이 안착되어 고속회전을 통해 원심력으로 기판의 미세한 부분까지 이물질이 제거되도록 하는 PCB기판 세청용 회전 지그를 개발 하였다. 결과는 다음과 같다. 개발 목표는 PCB기판 세척시 불량률을 줄이는 것으로 기존 침전식에서, 원심력을 이용한 회전형으로 개발, 세척액에 따른 기판손상을 80%이상 줄이는 결과를 얻었다. 회전식에 따른 세척할 수 있는 수량이 제한된 단점을 베이스플레이트에서 PCB기판의 용이한 탈부착이 가능하도록 설계 기존 방법의 세척 후 공정을 포함한 시간과 비교하여 큰 차이를 보이지 않았으며. 기존 시간과 비교하여 세척시간을 90%까지 높였다. 세척용 회전 지그에 고정된 PCB기판이 원심력에 의해 이탈현상 없이 고정력을 효과적으로 유지 할 수 있도록 설계함으로써, 세척공정의 안정성 및 신뢰성을 확보하여 불량률을 1% 미만으로 개선 할 수 있었다.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.11-15
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• 2020

In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.

• 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.

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

• 반도체디스플레이기술학회지
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• 제23권2호
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• pp.1-5
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• 2024

In the electronics industry, a lot of research and development is being conducted on electronic component supply, component alignment and insertion, and automation of soldering on the back side of the PCB for automatic PCB assembly. Additionally, as the use of electronic components increases in the automotive component field, there is a growing need to automate the alignment and insertion of components with leads such as transistors, coils, and fuses on PCB. In response to these demands, the types of PCB and parts used have been more various, and as this industrial trend, the quantity and placement of automation equipment that supplies, aligns, inserts, and solders components has become important in PCB manufacturing plants. It is also necessary to reduce the pre-setting time before using each automation equipment. In this study, we propose a method in which a vision system recognizes the type of component and simultaneously corrects alignment errors during the process of aligning and inserting various types of electronic components. The proposed method is effective in manufacturing various types of PCBs by minimizing the amount of automatic equipment inserted after alignment with the component supply device and omitting the preset process depending on the type of component supplied. Also the advantage of the proposed method is that the structure of the existing automatic insertion machine can be easily modified and utilized without major changes.

• 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.

• 전기학회논문지
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• 제61권3호
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• pp.472-478
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• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.

• 제어로봇시스템학회논문지
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• 제11권11호
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• pp.950-955
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• 2005

A automatic component inserting system for industrial PCB is developed in this paper. This system has not been developed in Korea. Most domestic companies produce PCB manually. This process requires highly-skilled staff. Therefor, we developed a PCB inserting system for automation of the process and improved productivity. There are low parts in this system; press, table, tool change and control part. A hybrid press cylinder with pneumatic and hydraulic is used in the press part. The table part consists of pneumatic actuators, stepping motors and ball-screw mechanism. In the tool change part, upper tools can be exchanged automatically for the inserting of various components. The control part consists of motor drivers, PLCs and power supply.

• 한국컴퓨터정보학회논문지
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• 제21권3호
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• pp.57-64
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• 2016

This paper deals with the PCB assembly time minimization problem that the PAP (pick-and-placement) machine pickup the K-weighted group of N-components, loading, and place into the PCB placement location. This problem considers the rotational turret velocity according to component weight group and moving velocity of distance in two component placement locations in PCB. This paper suggest heavy-weight component group first pick-and-place strategy that the feeder sequence fit to the placement location Hamiltonean cycle sequence. This algorithm applies the quadratic assignment problem (QAP) that considers feeder sequence and location sequence, and the linear assignment problem (LAP) that considers only feeder sequence. The proposed algorithm shorten the assembly time than iATMA for QAP, and same result as iATMA that shorten the assembly time than ATMA.