• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.625-632
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• 2024

This paper analyzed the changes in the curriculum of computer and software-related majors that educate the core ICT technologies needed for the 4th Industrial Revolution, before and after the COVID-19 pandemic. According to the standard classification of university education units, 172 majors classified into Applied Software Engineering, Computer Science·Computer Engineering, and Artificial Intelligence Engineering were targeted, and the curricula of 2023 and 2019 were compared and analyzed. As a result of the analysis, the introduction of the related curriculum for each curriculum group increased by about 2.6%p before and after the COVID-19 pandemic (2023 84.2%, 2019 81.6%). and the 4th Industrial Revolution response index increased by 9.5 points (37.0 in 2023, 27.5 in 2019)

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.67-72
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• 1997

How to measure technological level has concerned research analysists for a long time. Many methods exist, and they all have their advantages and disadvantages according to how they are used. The purpose of this study is to develop qualitative indicator to measure industrial technological level, in particular manufacturing capacity. In this indicator, the two basis of technology classification and the concept of the technology competitiveness were introduced. First, the types of technology are classified as three classes : material technology, processing technology and product technology. Second, the characteristics of technology are divided into the three categories : core technology, peripheral technology and sprouting technology On this basis, the qualitative technological level was made in terms of the competitiveness of it's manufacturing capacity. This study should be a practical approach for application of measuring of technological level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.35-42
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• 2008

In the national economy, rate of service industry is going up to compare with manufacture industry. In spite of getting lots of results to be introduced 6 sigma methodology in Korea, many service companies is suffering with trial and errors. Also 6 sigma isn't settled perfect yet. The reason for that, 6 sigma have been applied to various service without considering. Therefore, this research shows to you right practice plans for service industrial classification to check structural features and difference. So this research seeks methods for revitalization of 6 sigma methodology in service industry after checking existed research, case study for companies to be applied by 6 sigma. As the result, service industry is forecasted to contribute greatly in economic growth and employment enlargement through enlargement of service role in manufacturing industry production as well as by itself.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.559-571
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• 2015

To strengthen competences, most of firms have co-operated with external partners. This increases the possibility of unexpected conflicts between firms due to the intellectual property litigation. A suitable intellectual property strategy for firms has to be developed to settle this issue. This study aims to analyze an utilization of intellectual property strategy in firms, and tries to suggest a concept of IP roadmap to support intellectual property strategy planning aligned with technology planning process. For the purposes, we derive five types of intellectual property strategy of firms using Korea Innovation Survey. Then, we explore significant affecting factors using a decision-tree and conduct in-depth analysis for them. Lastly, we suggest a concept of IP roadmap, which can be a supporting tool for developing intellectual property strategy in firms, based on analysis results.

• 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 KIEE Conference
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• 1999.11d
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• pp.1000-1002
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• 1999

In this study, we were developed to provide a method for evaluating insulation systems for mold transformers with high-voltage ratings greater than 600V, in order to establish a uniform method for determining the temperature classification of mold transformer insulation system by testing rather than by chemical composition. Since these procedures are considered to be new, and have been tested exhaustively, further testing may prove the need for future revisions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.171-178
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• 2012

A possible heuristic to solve metropolitan area vehicle routing problems with variable vehicle speeds is suggested in this research. Delivery hours are classified into 4 different time zones to make variable vehicle speeds no change within the same time zone to make TDVRP simple to solve. The suggested heuristic consists of 2 stages such as initial solution development step and initial solution improvement step. A computer program using C++ is constructed to evaluate the suggested heuristic. Randomly generated vehicle routing problems are used for the experiments. This heuristic could be helpful to logistics companies by increasing delivery efficiencies since the 4 zone classification is taken from the observed traffic information offered by a local government.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.540-541
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• 2018

최근 특허분석의 중요성이 부각되고 있다. 특허분석을 위해 검색된 특허 중 노이즈 특허를 분류하는 작업은 많은 시간과 비용을 요구한다. 본 논문에서는 효율적인 특허분석을 위한 노이즈 특허 분류 성능의 비교를 진행한다. 그리고 비교한 결과를 통해 노이즈 특허 분류에 최적의 모형을 찾는 것을 목표로 한다. 듀얼 카메라 특허 603건을 이용하여 실제 실험을 실시한 결과, 나이브 베이지안 분류 모형의 분류 성능이 가장 우수하였다.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.51-59
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• 2006

So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.