• 산업공학
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• 제14권2호
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• pp.120-126
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• 2001

Virtual manufacturing is a technology facilitating effective development and agile manufacturing of products via sophisticated computer models representing physical and logical schema and behavior of real manufacturing systems including manufacturing resources, environments, and products. Based on these models, virtual manufacturing supports decision making and error checking in the entire manufacturing processes from design to mass production. At first, we analyzed manufacturing preparation activities of the four major production shops such as press, body assembly, painting and final assembly, of a Korean automotive company. We then developed the workflow models out of the analysis by the IDEF methodology, and generated a strategic plan for the systematic application of the virtual manufacturing technologies. We identified many manufacturing preparation activities that can be improved by the application of virtual manufacturing technologies. Finally, we estimated the effect of improvement including time savings in car development processes and corresponding cost savings.

• 자원리싸이클링
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• 제32권2호
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• pp.43-51
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• 2023

본 연구에서는 자동차엔진의 신품제조시와 재제조시 발생하는 환경영향을 전과정 관점에서 산정하고 이를 기반으로 온실가스 저감효과를 산정하였다. 자동차엔진 원부자재 원료취득 및 제조공정에서 배출되는 온실가스량은 신품제조시 약 3,473 kg, 재제조시 약 872 kg으로 재제조를 통해 저감되는 온실가스량은 약 2,601kg으로 나타나 폐기 단계를 제외한 전과정 측면에서 저감효과가 있는 것으로 분석되었다. LCA 가중화 분석 결과 신품 제조시 환경영향은 1.07E+03 Eco-point, 재제조시 2.67E+02 Eco-point로 나타났으며, 주요 6대 영향 범주 중 지구온난화 점유비율이 99.72%, 99.68%로 높게 나타났다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권9호
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• pp.393-402
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• 2015

데이터 시각화 기술은 다양한 데이터와 그 분석 결과를 쉽게 이해할 수 있도록 도와줌으로써 제조현장과 같은 실제 산업현장에서도 그 유용성이 기대되고 있다. 제조현장에서 발생하는 대량의 데이터는 제조 기술의 표준화를 위한 기반 데이터가 될 수 있으며 제조공정의 개선을 위하여 매우 중요한 역할을 수행할 수 있다. 본 논문에서는 실험계획법과 데이터 분석 기반의 제조공정 최적화를 위한 정보 시각화 방법을 제안한다. 데이터 분석 결과의 정보 시각화를 통하여 작업 현장에 이해하기 쉬운 분석 결과를 제공함으로써 다양한 불량원인을 감소시키고 제조공정을 개선시킬 수 있다.

• International Journal of Aerospace System Engineering
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• 제4권1호
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• pp.9-12
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• 2017

In this study, an investigation on mechanical properties of flax natural fiber composite is performed as a precedent study on the design of eco-friendly structure using flax natural fiber composite. The Vacuum Assisted Resin Transfer Molding-Light (VARTML) manufacturing method is adopted for manufacturing the flax fiber composite panel. The VARTML is a manufacturing process that the resin is injected into the dry layered-up fibers enclosed by a rigid mold tool under vacuum. In this work, the resin flow analysis of VARTM manufacturing method is performed. A series of flax composite panels are manufactured, and several kinds of specimens cut out from the panels are tested to obtain mechanical performance data. Based on this, structural design of chemical storage tank for agricultural vehicle was performed using flax/vinyl ester. After structural design and analysis, the resin flow analysis of VARTM manufacturing method was performed.

• 소성∙가공
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• 제12권2호
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• pp.110-115
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• 2003

This paper is concerned with the compression test and forming process of flange by using virtual reality and analysis(simulation) program. This virtual manufacturing can be carried out one personal computer without any expensive devices for experiment. The virtual manufacturing composed of three modules such as the imput, calculation and the output modules on internet. Internet user can give the material's property and process parameters to the sever computer at the input module. On the calculation module, a simulator computes the virtual manufacturing process by analysis program and stores the data as a file. The output module is the program in which internet user can confirm virtual manufacturing results by showing tables, graphs, and 3D animation. This programs is designed by an internet language such as HTML, CGI, VRML and JAVA ,while analysis programs use the finite increasing, the virtual manufacturing technique will substitute many real experiments in the future.

• 산업경영시스템학회지
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• 제24권64호
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• pp.77-83
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• 2001

In this paper, we investigated the relationship between the variables related to manufacturing environment and industrial accident. Also we wish to analyze how much these variables influence in production result of company: the manufacturing performances such as production quantity, quality, cost and delivery. For this investigation, we collected the real data from 16 small/medium-sized manufacturing companies by performing a questionnaire survey and one-site interview with the workers. Sixteen companies were made up of the following four industries: metal processing, machinery manufacturing, chemical products manufacturing and electronic products manufacturing, The data analysis was made using SPSS PC+. Based on the result of the analysis, we came to the conclusion that most of variables related to manufacturing environment and industrial safety were connecting with industrial accident occurrence and also influenced in manufacturing performance.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.168-173
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• 2022

As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1992년도 제2회 학술발표회
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• pp.119-155
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• 1992

Traditionally, the target of manufaturing technology strategy was derived in a efficiency, cost and productivity. So most activities of the manufacturing brought focus into the engineering technology, equipments and research and improvement of new products to maximize the efficiency. As a resell of this legacy, most of the activities of manufacturing has been executed on the method of quality improvement, development of new equipment to incense the efficiency and the research of materials for new products. Those trends, however overlook the operation management activities which is very important as a assets in competitive strategy. But the market enviornment of morden manufacturing companies faced to the uncertainty and complexity. So they need capability of competition which requires new concept of manufacturing technology strategy to grasp the competitive advantages. In this point of view, this paper deal with the empirical study in korean manufacturing technology strategy of the electic and electronic industry. For the empirical study, check list was made to survey the 98 manufacturing companies. The analysis procedures are as below. First, identify the manufacturing technology group an product structure group by each variable. Second manufacturing technology variables are segmented into product technology and vertical integration, suborder and infrastructure, to analyse the decision making pattern which derive the strategy groups. Third, by the fitness analysis between product structure group and manufacturing technology group, the economic results of a growth rate of sale and a profit rate of sale are tested. In this approach, fitness analysis between product structure group and manufacturing technology group show, as a whole, the no significant values in economic results of the company. But investigating the statistical values shows the trend that econmic result of the complany is somewhat higher when the degree of fitness of manufacturing technology strategy by product structure has high value. Concluding the remarks, the competitive advantages of company lies not in the efficiency of manufacturing systems but in the way of the structure and decision making pattern of the manufacturing system. And the cons i stoney between strategy target and manufacturing technology strategy, and the consistency of manufacturing technology strategy and product structure are the term of competitive advantages.

• 한국CDE학회논문집
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• 제19권2호
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• pp.138-147
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• 2014

In manufacturing companies, different types of production have been developed based on diverse production strategies and differentiated technologies. The production systems have become smart, factories are filled with unmanned manufacturing lines, and sustainable manufacturing technologies are under development. Nowadays, the digital manufacturing technology is being adopted and used in manufacturing industries. When this technology is applied, a lot of efforts, time and cost are required and training professionals in-house is limited. In this paper, we introduce e-FEED system (electronic based Front End Engineering and Design) that is the integrated design and analysis system for optimized manufacturing line development on virtual environment. This system provides the functions that can be designed easily using library and template based on standardized modules and analyzed automatically the logistic and capacity simulation by one-click and verified the result using visual reports. Also, we can review the factory layout using automatically created 3D virtual factory and increase the knowledge reuse by e-FEED system.

• 한국빅데이터학회지
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• 제1권1호
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• pp.41-51
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• 2016

정보통신 기술의 발달로 과거에는 다룰 수 없었던 대용량의 데이터 처리가 가능해지면서 빅데이터의 관심이 고조되고 있다. 제조 산업은 축적된 데이터가 풍부하여 빅데이터의 적용 및 활용이 가장 기대되는 분야이다. 제조 기업의 공정은 생산설계, 생산, 판매 등의 프로세스가 복잡하게 얽혀있기 때문에 품질 관리와 생산효율성의 증대를 위해 제조 공정 프로세스의 효율화가 중요하다. 본 연구에서는 빅데이터 기술과 프로세스 마이닝 기법을 제조 공정 분석에 접목시킨 빅데이터 클라우드 서비스를 제안한다. 제조 기업은 클라우드 서비스를 활용하여 공정 프로세스의 개선 및 비용절감 등의 효과를 거둘 수 있다. 빅데이터 클라우드 서비스는 공정 프로세스 분석, 공정 시간 분석 등의 다양한 분석 서비스를 제공하며 구현 완료하였다. 사례 연구를 통해 클라우드 서비스의 유효성을 검증하였다.