• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.190-195
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• 1997

Abstract: In this paper,an autoematic gear inspection system has been been developed using the computer aided vision system. Image processing and data analysis algorithms for gear inspection have been investigated and shown to perform quickly with high accuracy. As a result,dimensions of a gear can be measured upto few micrometer size in real time. In addition, the system can be applied to a practical manufacturing process even under nosiy conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.6-101
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the product(bad pallets). An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labeling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets ...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.485-489
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• 1996

In this paper, an automatic gear inspection system has been developed using the computer aided vision system. Image processing and data analysis algorithms for gear inspection have been investigated and were shown to perform quickly with high accuracy. As a result, dimensions of a gear can be measured upto few micrometer size in real time. In addition, the system can be applied to a practical manufacturing process even under noisy conditions.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.343-348
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• 1992

Using the real-time image processing technique, we have developed an automatic visual inspection system which detects the defects of the surface muonted components in PCB( missing components, mislocation, mismounts, and reverse polarity, etc ) and collects the quality control and production management data. An image processing system based on a commercial parallel processor, TRANSPUTER by which the image processing time can be largely reduced was designed. Analyzing the collected data, the proposed inspection system contributes to the productivity improvement throughthe reduction of defective rate.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.37-43
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• 2004

The purpose of this study is to develop a practical image inspection system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from $30^{\circ}$ to $45^{\circ}$ simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment, the image inspection system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94% to 96%. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automation when the image inspection system developed from this research is applied to the productive field.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.666-672
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• 2011

In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1177-1183
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• 2013

In this paper, the analysis of inspection period bases on reliability is suggested in the field of traction power system. Even though there are several maintenance models, the most commonly used maintenance assessment has been focused on time based maintenance in real traction power systems. The maintenance intervals are selected on the basis of long-time experience. It ensures high availability and exact planning of staff. Reliability centered maintenance, which evaluates criticality and severity of each failure mode, achieves the operation, maintenance, and cost-effective improvement that will manage the risks of equipment. This paper deals with electrification in railway inspection frequency and applied reliability based inspection frequency instead of constant intervals. The distribution function of failure rate in traction power system belongs to Weibull function. Also, the fault data and the number of installed equipments for electrifications are collected. The failure history is investigated and classified in detail. Though these complicated procedures, it contribute to extend equipment lifetime and to reduce maintenance costs.

• Journal of the Korean Society for Railway
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• v.5 no.2
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• pp.104-111
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• 2002

The purpose of interlocking system was to prevent the route for a train being set up and its protecting signal cleared if there was already another, conflicting route set up and the protecting signal for that route cleared. This paper proposed Interlocking Inspection System(IIS) consisting of interlocking simulator and field simulator to operate interlocking test of computer based Electronic Interlocking System(EIS) in this paper. Interlocking simulator consists of Design Edit System(DES), Logical Database Management Tool(LDMT) and real-time confirming system, field simulator is a equipment to simulate a control object of EIS and constitutes configuration operated in 19 inch standard rack. As a result of test to prove capacity of this IIS, the efficiency was shown as excellent. Therefore by using inspection system, we obtain every advantages. It has the functions for test data generation and automatic test execution based on personal computer. Time and cost for test work can be reduced more efficiently by using this developed inspection system

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.369-378
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• 2018

This study proposes a new approach to real time implimemtation of shape recognition technology of die casting and forging parts based on robot vision for smart factory. The proposed shape recognition and inspection technology for forging and die casting parts is very useful for manufacturing process automatiom and smart factory including external form's automatic inspection of machanical or electronic panrs for the precision verification. The reliabiblity of proposed technology Ihas been illustrated through experiments.