• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.604-611
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• 2013

This paper presents an second harmonic elimination method based on the impedance variation scheme. Through the power quality analysis from the nonlinear loads connected on the power system, the second harmonic problems have been analyzed with a case study analysis and the experiments. In the paper, the second Harmonic generation was simulated with a single phase SCR rectifier and the analytical model is proposed for the second harmonic generation. A novel impedance variation scheme is proposed and analyzed to eliminate the second harmonic. The experiment has been performed on the 60(MVA) industry manufacturing plant. The experimental result demonstrates the proposed impedance variation scheme successfully operate on the 60(MVA) industry manufacturing plant.

• KDI Journal of Economic Policy
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• v.37 no.3
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• pp.31-53
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• 2015

According to the macroeconomic allocation efficiency measure, particularly based on the methodology of Hsieh and Klenow (2009), Korea's allocation efficiency in the manufacturing industry deteriorated in the 2000s compared to that in the 1990s. This study compares the potential TFP gain when resource allocation is removed, an indicator of allocation inefficiency according to Hsieh and Klenow (2009), and the productivity dispersion in the Korean manufacturing industry. It finds that the TFP gain may be better explained by TFP dispersions rather than proxies related to factors of distortion. The findings imply that we should investigate the sources of TFP dispersion rather than the sources of distortion to explain increases in the TFP gain (or TFP loss), which is considered as allocation inefficiency in the literature.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.572-578
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• 2015

Yield prediction is one of the most important issues in semiconductor manufacturing. Especially, for a fast-changing environment of the semiconductor industry, accurate and reliable prediction techniques are required. In this study, we propose a prediction model to predict wafer yield based on virtual metrology process parameters in semiconductor manufacturing. The proposed prediction model addresses imbalance problems frequently encountered in semiconductor processes so as to construct reliable prediction model. The effectiveness and applicability of the proposed procedure was demonstrated through a real data from a leading semiconductor industry in South Korea.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.633-634
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• 2006

Recently we started a development of the digital meister expert system for the product design supporting in manufacturing industry. Knowledge representation is of major importance in digital moister expert system. This rule-based expert system-knowledges are designed for a certain type of knowledge representation such as rules or logic. The way in which a rule-based expert system represents knowledge affects the development, efficiency, speed, and maintenance. Eventually, this digital moister system is used to the engineer in manufacturing industry for the process control, production management and system management. In this paper, we propose the digital moister system knowledge representation method for product design supporting in manufacturing industry and we present introduction and contents of rule-based knowledge representation supporting tool.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.292-304
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• 2011

This study is to search for the core factors of improving competitiveness of small and medium venture manufacturing company in electric and electronic industry and to do an in-depth analysis of the relations with management performance through systematic approach and to provide implications of importance of the management for the improvement factors for the domestic small and medium venture manufacturing company in electric and electronic industry. The report is analyzed how the relationship between the quality management system that was discussed in existing literature and the core factors of absorbing capability impact to the enterprise management performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.143-154
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• 1996

Manufacturing industry is on the verge of a major paradigm shift. This shift will take us away from mass production, way beyond lean manufacturing into a world of new intelligent and agile manufacturing. We spent most of our time during the 1980s copying the Japanese. This paper studys reengineering methodologies to build up low-cost manufacturing systems efficiently in Korean companies

• Korea Trade Review
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• v.41 no.5
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• pp.353-371
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• 2016

The purpose of this paper is to examine the structural change of Korean manufacturing industries and the differences of total factor productivity(TFP) between exporting industries and import substituting industries in Korean manufacturing industry from 1980 to 2013. The empirical results show that over half of total 13 industries have experienced changes of direction from import to export or export to import, which implies that there was a considerable structural change in Korean manufacturing industry. The output growth rates are higher in exporting industries than in import substituting industries. All industries employ more capital than labor during the period, which means that production methodology in Korean industries changes to a more capital intensive one. Finally, the growth rate of total factor productivity is higher in exporting industries than in import substituting industries, and it is also proved in panel regression analysis.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1070-1075
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• 2004

Many mid-sized companies in Korean automotive industry have attempted to solve the lack of human power, to control the quality of components, to improve the production rate, and to innovate the manufacturing line. The goals of this study are to analyze the production rate of an automotive component manufacturing line using simulation software, to construct a Flexible Automation Subassembly (FAS) system and to suggest an optimized layout design using FAS line. In this research, the simulation model for manufacturing line was developed and used the realistic data (production planning, component type, working order, process time, queue time, line rules, etc) of a medium sized company in Korean automotive industry. To complete this research, a simulation software 'ARENA' was used.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.364-372
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• 2007

The cost modeling of the LCD manufacturing system with the repair and the rework process is hard to achieve because of it's complex manufacturing process. The technical cost modeling divides each process separately and hierarchically, so it is very useful to calculate the total manufacturing cost of the complex manufacturing system. We applied the method to the complex LCD manufacturing system to obtain more accurate cost model. Yields are the most important control parameters in manufacturing. In this paper, we propose a yield based cost model for the LCD manufacturing system and reveal the relationship between manufacturing yield and cost. Through the model, we can estimate the manufacturing cost on the basis of yields that are control indicators of manufacturing. Some simulations are performed to observe the effects of the yield to the cost, and the results are coincide with the real situation. With the proposed model, we expect to develop some optimization problems for enlarging productivity in the LCD industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.81-101
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• 2003

The financial statements purpose to provide useful information to decision-making process of business managers. The value-relevant information, however, embedded in the financial statement has been often overlooked in Korea. In fact, the financial statements in Korea have been utilized for nothing but account reports to Security Supervision Boards (SSB). The objective of this study is to develop earnings forecasting models through financial statement analysis using artificial intelligence (AI). AI methods are employed in forecasting earnings: artificial neural networks (ANN) for manufacturing industry and case~based reasoning (CBR) for banking industry. The experimental results using such AI methods are as follows. Using ANN for manufacturing industry records 63.2% of hit ratio for out-of-sample, which outperforms the logistic regression by around 4%. The experiment through CBR for banking industry shows 65.0% of hit ratio that beats the statistical method by 13.2% in holdout sample. Finally, the prediction results for manufacturing industry are validated through monitoring the shift in cumulative returns of portfolios based on the earning prediction. The portfolio with the firms whose earnings are predicted to increase is designated as best portfolio and the portfolio with the earnings-decreasing firms as worst portfolio. The difference between two portfolios is about 3% of cumulative abnormal return on average. Consequently, this result showed that the financial statements in Korea contain the value-relevant information that is not reflected in stock prices.