• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.625-632
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• 2002

We propose an outsole measurement/inspection system to improve the quality of the shoe product. It uses the Divide-and-Conquer technique to measure the length of shoes'outsole. First, it detects edge positions of outsole's toe and heel from each image frame using an unique scale block we defined and calculates the outsole's length as the distance of two edge positions. Then it compensates the total length of outsole using the side image of outsole. Next, it classifies the outsole as inferior goods if the measurement error is bigger than 5.8mm. As a result of testing with the various kinds of outsoles, it was shown that the 95% accuracy was acquired within 1mm allowable error range. In conclusion, the proposed inspection system is effective and useful in the measurement/inspection process of shoe product and any material object as well.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.11-16
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• 2021

In this paper, a quality inspection system was developed to identify the defective assembly of connectors used in automobile wiring. For waterproof connectors, an internal seal must be inserted for waterproofing. However, there are cases where it is omitted or double-inserted during production. An automatic inspection jig was designed using photosensors and touch switches to classify good and bad connector components. In the case of the existing visual inspection, 6,400 connectors were inspected when 5 people inspected for 8 hours. However, when using the inspection jig developed under the same conditions, 20,000 pieces were inspected. In other words, the productivity is greatly improved compared to the conventional visual inspection.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.162-165
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• 2007

TFT-LCD process has two advantages as compared with the semiconductor-process. It is that cycle time is short and number of the final products are small. But it needs complicated inspection / assembly line to be treated manually and much higher labor costs in the TFT-LCD process. Also, It is necessary to build PICS(Production Information and Control System) which is automated and intelligent. In this paper, an automated process of LCD module assembly line that can increase productivity and reduce the cost of production to strengthen the competitiveness corresponding with global market is planned in comparison with its manual/semi-auto. It is noted that The automated line for COG$\sim$FOG process replacing with the existing facilities had the following effects; the productivity is increased to about 1.5 times and labor cost reduced 85%. In addition, whole assembly line can be short and simple.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.139-142
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• 2000

$\mu$BGA(Ball Grid Array) is growing in response to a great demand for smaller and lighter packages for the use in laptop, mobile phones and other evolving products. However it is not easy to find its defect by human visual due to in very small dimension. From this point of view, we are interested its development of a vision based automated inspection algorithm. For this, first a 2D view of $\mu$BGA is described under a special blue illumination. Second, a notation-invariant 2D inspection algorithm is developed. Finally a 3D inspection algorithm is proposed for the case of stereo vision system. As a simulation result, it is shown that 3D defect not easy to find by 2D algorithm can be detected by the proposed inspection algorithm.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.3
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• pp.275-281
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• 2004

Socket weldment used to change the flow direction of fluid nay have flaws such as lack of fusion and cracks. Liquid penetrant testing or Radiography testing have been applied as NDT methods for flaw detection of the socket weldment. But it is difficult to detect the flaw inside of the socket weldment with these methods. In order to inspect the flaws inside the socket weldment, a ultrasonic testing method is established and a ultrasonic transducer and automated ultrasonic testing system are developed for the inspection. The automated ultrasonic testing system is based on the portable personal computer and operated by the program based Windows 98 or 2000. The system has a pulser/receiver, 100MHz high speed A/D board, and basic functions of ultrasonic flaw detector using the program. For the automated testing, motion controller board of ISA interface type is developed to control the 4-axis scanner and a real time iC-scan image of the automated testing is displayed on the monitor. A flaws with the size of less than 1mm in depth are evaluated smaller than its actual site in the testing, but the flaws larger than 1mm appear larger than its actual size on the contrary. This tendency is shown to be increasing as the flaw size increases. h reliable and objective testing results are obtained with the developed system, so that it is expected that it can contribute to safety management and detection of repair position of pipe lines of nuclear power plants and chemical plants.

• Journal of Platform Technology
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• v.11 no.6
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• pp.13-20
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• 2023

Regularly inspecting vehicle tires' condition is imperative for driving safety and comfort. Poorly maintained tires can pose fatal risks, leading to accidents. Unfortunately, manual tire visual inspections are often considered no less laborious than employing an automatic tire inspection system. Nevertheless, an automated tire inspection method can significantly enhance driver compliance and awareness, encouraging routine checks. Therefore, there is an urgency for automated tire inspection solutions. Here, we focus on developing a deep learning (DL) model to predict cracked tires. The main idea of this study is to demonstrate the comparative analysis of DenseNet121, VGG-19 and EfficientNet Convolution Neural Network-based (CNN) Transfer Learning (TL) and suggest which model is more recommended for cracked tire classification tasks. To measure the model's effectiveness, we experimented using a publicly accessible dataset of 1028 images categorized into two classes. Our experimental results obtain good performance in terms of accuracy, with 0.9515. This shows that the model is reliable even though it works on a dataset of tire images which are characterized by homogeneous color intensity.

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.83-88
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• 2021

Recently, due to the aging of workers and the weakening of the labor base in the automobile industry, research on quality inspection methods through ICT(Information and Communication Technology) convergence is being actively conducted. A lot of research has already been done on the development of an automated system for quality inspection in the manufacturing process using image processing. However, there is a limit to detecting defects occurring in the automotive sunroof sealer application process, which is the subject of this study, only by image processing using a general camera. To solve this problem, this paper proposes a system construction method that collects image information using a infrared thermal imaging camera for the sunroof sealer application process and detects possible product defects based on the SVM(Support Vector Machine) algorithm. The proposed system construction method was actually tested and applied to auto parts makers equipped with the sunroof sealer application process, and as a result, the superiority, reliability, and field applicability of the proposed method were proven.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.42-50
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• 2008

We developed a visual inspection system for detecting defective products. Most existing inspection systems are designed to be dedicated to one product, which makes operator spend extra money and time to adopt other products. In this work, we propose a flexible visual inspection system that can inspect various products without any additional major job at a low-cost. The developed system contained image processing algorithm libraries and user-friendly graphic interface for adaptable image-based inspection system. We can find a proper threshold value using the proposed algorithm which uses correlation coefficient between a non-defective product and existing sample images of defective product. And We tested the performance of the proposed algorithm using Otsu's method. The proposed system is applied to a automated inspection line for cellular phone.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.84-90
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• 2004

Today, automobile world market is highly competitive. In order to strengthen the competitiveness, quality of automobile is recognized as important and efforts are being made to improve the quality of manufactured components. The directional ability of automobile has influence on driver directly and hence it must be solved on the preferential basis. In the present research, an automated vision system has been developed to inspect the front chassis module. To interpret the inspection data obtained for front chassis module, new interpreting algorithm have been developed. Previously the control of tolerance of front chassis module was done manually. With the help of the new algorithm developed, the dimension is calculated automatically to check whether the front chassis module is within the tolerance limit or not.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.