• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.317-325
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• 2022

In this study, we propose a technological system designed to provide machine vision-based automatic inspection and autonomous operation services for an entire process related to product inspection in wire harness manufacturing. The smart factory paradigm is a valuable and necessary goal, small companies may encounter steep barriers to entry. Therefore, the best approach is to develop towards this approach gradually in stages starting with the relatively simple improvement to manufacturing processes, such as replacing manual quality assurance stages with machine vision-based inspection. In this study, we consider design issues of a system based on the proposed technology and describe an experimental implementation. In addition, we evaluated the implementation of the proposed technology. The test results show that the adoption of the proposed machine vision-based automatic inspection and operation service system for multi-wire harness production may be considered justified, and the effectiveness of the proposed technology was verified.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.1
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• pp.59-63
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• 2014

Elliptical gears are used in the oval flowmeter and oval flow meter inspects volume of water thanks to space by the elliptical shape. The purpose of this study is to judge accuracy of processing of the elliptical gear and develop inspection system using machine vision. Demand of machine vision is increasing while the factory automation is spreading and principle factor in-process inspection. But, gear inspection using the machine vision rarely used because of complex shape of gear. In this study, it seems possible that elliptical gear is inspected by inspection software using machine vision and inspection program can judge accuracy of processing of the elliptical gear designed this study.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.184-191
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• 2004

In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1558-1563
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• 2010

This paper describes a study on algorithm for the development of machine vision system as well as the inspection of automobile's plastic part locking lever to replace a human worker's eye inspection. Before developing the machine vision system based on the PC, the purpose of this research is to develop the algorithm to decide whether a product is a good/bad one in real time inspection. NI-LabVIEW software is used in the inspection method and an inspection program is developed using LabVIEW Vision image functions. The inspection program was built and validated to help the system operator set up the inspection area and change the criteria number in the program.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.698-704
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• 2010

The machine vision system has been widely applied at automatic inspection field of the industries. Especially, the machine vision system shows good performance at difficult inspection field by contact method. In this paper, the automatic system of a slant method to inspect screw/bolt shape using machine vision is developed. The inspection system uses pattern matching method that search similar degree of the lucidity, the average lucidity, length and angle of inspection set up area using a circular scan and a line scan method. Also the feeding method for inspection product is the slant method, and feed rate is controlled by the ramp angle adjustment. This inspection system is composed of a feeding device, a transfer device, vision systems, a lighting device and computer, and is composed the sorting discharge system of the inferior product. The performance test carried out the feeding speed, the shape correct degree and the sorting discharge speed according to the type of screw/bolt. This sorting inspection system showed a satisfied test results in whole inspection items. Presently, this sorting inspection system is being used in the manufacturing process of screw/bolt usefully.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.125-130
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• 2013

In this paper, in order to overcome shortcomings of manual inspection for the automotive PWM Shaft, we developed an automated inline inspection system. The automated inline inspection system consists of the work feeder unit, conveying unit, outer diameter check unit, run-out and roundness check unit, machine vision, defective separation unit and status alarm unit. We used the machine vision system for automatic inspection process and designed the inline systems for automatic feeding and selecting process. Also the repeated operation test was performed in order to verify the precision and reliability of the proposed automated inline inspection system.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.145-146
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• 2008

The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight cannot bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we proposed histogram specification in this paper for machine vision inspection accuracy. As a result of histogram specification algorithm, we could increase the exactness of visual inspection and prevent system error from physical and spirit condition of human. More specifically, average inspection error rate was 7.5[%] in existing inspection method but we could see 0.6[%] error rate after applying the algorithm which is presented in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1384-1390
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• 2019

This paper proposes a technological solution for improving the recognition direction of target objects for automatic vision inspection by machine vision. This paper proposes a technological solution for improving the recognition direction of target objects for automatic vision inspection by machine vision. This enables the automatic machine vision inspection to detect the image of the inspection object regardless of the position and orientation of the object, eliminating the need for a separate inspection jig and improving the automation level of the inspection process. This study develops the technology and method that can be applied to the wire harness manufacturing process as the inspection object and present the result of real system. The results of the system implementation was evaluated by the accredited institution. This includes successful measurement in the accuracy, detection recognition, reproducibility and positioning success rate, and achievement the goal in ten kinds of color discrimination ability, inspection time within one second and four automatic mode setting, etc.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.11-13
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• 2007

The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight can't bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we have used a power-law transformation in this paper. for improvement of vision inspection accuracy and could increase inspection accuracy of vision system. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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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.