• International Journal of Quality Innovation
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• v.7 no.3
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• pp.58-69
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• 2006

This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.1-19
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• 1994

There have been few studies which deal with the linkage between a corporate strategy and its management control system. Especially, no empirical study has been done in Korea to figure out if management control systems of Korean companies are designed and implemented to support companies' objectives and strategies. Based on the survey results of 68 companies we empirically tested if Korean companies are implementing appropriate control systems to complement their Quality strategies. Two representative quality strategies were classified into ECL(Economic Conformance-Level) and ZD(Zero-Defect) strategy. It was measured by a set of seven attitude questions addressing whether the managers adhered to ECL strategy or ZD Quality strategy. In addition, we checked if there is a difference m the level of commitment to the quality depending on the adoption of quality cost system. The results partly support the second hypothesis and regarding the first analysis we can conclude that there is not a strong linkage between Korean companies' ZD strategy and their management control systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.197-209
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• 2004

A company wishes to obtain a competitive edge by adopting an efficient logistics information system to control the logistics management process. The elements of the competitive edges a company targets are to maintain good quality, reduce cost and on-time delivery and those competitive edges are closely related to the cycle time of a product. The logistics information system in a company is also closely tied with other business activities than the logistics itself. Therefore it is essential to choose a system that will help rationalize the logistics but also overall business operations along the supply chain from manufacturing to distribution of the products. This paper aims to research and analyze a problem with a logistics information system through case study and to suggest a logistics information system with RFID in place adopted to eliminate problems such as damages, loss and defect rates.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.189-201
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• 1999

On November, 1998, Ministry of Finance and Economy in Korea announced officially to enforce the PL(Product Liability) Law within the country at the first half of the year 2000. Therefore, a companys responsibility for customers who are damaged by a defect in the products safety will be gradually strict and impose burden on management. This paper presents suggestions about PL prevention of domestic enterprise through the research of PL prevention strategies and prevention systems in the USA and Japanese leading enterprises.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.211-222
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• 1999

6 Sigma is defined as the state of "defect free quality" with only 3.4 defective, goods out of 1 million. Samsung Display Device(SDD) was quick to embark on a new way of quality innovation. The goals of 6 Sigma campaign are established on the foundation of customer satisfaction such as quality, cost and service. Production field of SDD has a special 6 Sigma campaign, SQM(Standard Quality Management). Quality qualification system is introduced and implemented with strong reinforcement. C-S-I(Chart-Solve-Implement) model which was made by Dr. Bajaria(1991) is adopted for the project. All the workers of company will be encouraged to participate in the drive.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.79-101
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• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.63-70
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• 2019

The subject of the simultaneous measuring system of base pattern and deposition pattern is a new research topic on a defect inspection of OLED. In this paper, we propose a new OLED inspection method that simultaneously measures standard and deposition pattern images. This method reduces unnecessary processes and tac time during OLED inspection. For an additional reduction of the tac time during pattern measurement, the ROI was configured to measure only in the designated ROI area instead of measuring the entire area of an image. During the ROI set-up, the value of effective deposition pattern area is included so that if the deposition pattern is out of the ROI zone, it would be treated as a defect before measuring the size and center point of the pattern. As a result, the tac time and inspection process could be shortened. The proposed method also could be applied to the OLED manufacturing process. Production of OLED could be increased by reducing tac time and inspection process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.60-70
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• 2021

Recently, with the development of technologies for the fourth industrial revolution, convergence and complex technology are being applied to aircraft, electronic home appliances and mobile devices, and the number of parts used is increasing. Increasing the number of parts and the application of convergence technologies such as HW (hardware) and SW (software) are increasing the No Defect Found (NDF) phenomenon in which the defect is not reproduced or the cause of the defect cannot be identified in the subsequent investigation systems after the discovery of the defect in the product. The NDF phenomenon is a major problem when dealing with complex technical systems, and its consequences may be manifested in decreased safety and dependability and increased life cycle costs. Until now, NDF-related prior studies have been mainly focused on the NDF cost estimation, the cause and impact analysis of NDF in qualitative terms. And there have been no specific methodologies or examples of a working-level perspective to reduce NDF. The purpose of this study is to present a practical methodology for reducing NDF phenomena through data mining methods using quantitative data accumulated in the enterprise. In this study, we performed a cluster analysis using market defects and design-related variables of mobile devices. And then, by analyzing the characteristics of groups with high NDF ratios, we presented improvement directions in terms of design and after service policies. This is significant in solving NDF problems from a practical perspective in the company.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.43-49
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• 2004

Defects inspection of commodities are very important with those design and manufacturing process and essential to strengthen the competitiveness of those. If on-line automatic defects detection is performed without damaging to products, the production cost shall be curtailed through the reducing man-power, economical management of Q.C(Quality Control). In this paper, it is suggested three spatial filtering methods which can extract the necessary information in case of defects being on the surface of object like iron plate. In addition, the dependence of filtering characteristics on parameters such as the pitch and width of slits is analyzed and the surface defect detection system is constructed. Several experiments were carried out for determining the adequate spatial filtering method through comparing and analyzing effects of parameters like defect's size and shape, intensity of light, noise of coherent source and slit number.