• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2567-2572
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• 2014

In the present study, we aimed to obtain multi jig that PCB sheet with several PCB component can cut in a short time as to the Separation of PCB component. PCB supporter designed safely at the base frame and each model can be separable. it completed the neodium magnet for the fixing of the upper part laser transmission hole of the both. One of the development, the cutting working with one base frame which PCB component of various standard, fixing of module and bridge connected to PCB component could be possible. and it reduced the inconvenience which has to replace the base frame and PCB sheet fixed member. It compared to other press up about 70% of accuracy and a reduction in investment cost was about 400%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4736-4741
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• 2014

This study examined PCB component cleaning on a PCB component surface, which has defects of precipitation type washing (existing rinse method), sealant and foreign material formed in the adhesive process that could not be removed easily. The spin jig was developed for PCB component cleaning, in which the PCB component settled down, to solve the conventional problem of the removal of foreign material with the centrifugal force by high speed rotation. The results are as follows. With decreasing fraction defect in PCB component washing, the development and substrate damage decreased by more than 80% according to the abstergent in the rotary type using the centrifugal force in the existing precipitation type. When the base plate showed a large difference with the time to include the process after washing the design using the existing method, easy attachment and separation of the PCB component could be possible. The washing time was enhanced 90% compared to the existing time. The reliability of the security and washing collaboration of the design and stability of the cleaning process could be secured so that there was no phenomenon of secession, the PCB component fixed for a cleansing rotation jig could maintain a fixed force by the centrifugal force. The stability and reliability of the washing process and the defective rate could be improved to less than 1%.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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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.

• Journal of Korea Multimedia Society
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• v.24 no.8
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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.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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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.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.632-635
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• 2004

PCB assembly is a complicated and difficult process to optimize due to the necessity of simultaneous consideration of rack assignment and board mounting sequencing. An efficient component mounting method is developed using component gathering phenomenon. It is found that same components are located closely each other by checking PCBs in field and interviewing PCB designers. A new method counting this phenomenon is developed and it is performed better with more number of total components and more number of gathered components cases. Simulation models are developed using Visual C++ for performance evaluation of the heuristic.