• 한국기후변화학회지
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• 제5권3호
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• pp.189-197
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• 2014

Carbon footprint of apple was a sum of $CO_2$ emission in the step of manufacturing waste of agri-materials, and greenhouse gas emission during apple cultivation. Input amount of agri-materials was calculated on 2007 Income reference of Apple by Rural Development Administration. Emission factor of each agri- materials was based on domestic data and Ecoinvent data. $N_2O$ emission factor was based on 1996 IPCC guideline. Carbon dioxide was emitted 0.64 kg $CO_2$ to produce 1 kg apple fruit, and carbon dioxide was emitted 43.6% in the step of the manufacturing byproduct fertilizer, 1.3% in the step of the manufacturing single fertilizer, 4.7% in the step of the manufacturing composite fertilizer, 6.3% in the step of the manufacturing agri-chemicals, 14.6% in the step of the manufacturing fuel, 11.5% in the step of the fuel combustion, 17.7% of $N_2O$ emission by nitrogen application and 0.18% of disposal of agri-materials. It is needed for farmers to use fertilization recommendation based on soil testing (soil. rda.go.kr) because scientific fertilization is a major tools to reduce carbon dioxide of apple production. The fertilization recommendation could be also basic data in Measurable-ReporTablele-Verifiable (MRV) system for carbon footprint.

• 한국전자거래학회지
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• 제21권1호
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• pp.91-104
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• 2016

e-비즈니스에서 데이터 분석과 시각화 등을 통한 비즈니스 인텔리전스가 각광받고 있다. 특히 빅데이터 기술이 관심을 받으면서 분석결과의 시각화도 중요하게 다뤄지고 있다. 기업 관리자들은 데이터 분석의 결과를 의사결정 과정에서 활용하길 원하며, 시각화 기법이 인지 기능과 운영 기능에서 도움을 주기 때문이다. 본 논문은 제조업에서 정보시각화 기술의 활용사례, 현황과 주요 이슈를 기존 연구문헌을 검토하여 분석하였다. 프로세스 모니터링, 의사결정 지원등에서 유용하게 사용될 수 있음을 확인할 수 있었고, 정보시각화 적용을 고민하는 제조 분야의 개발자 및 관리자 등에게 도움이 될 것으로 기대된다.

• 대한산업공학회지
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• 제38권1호
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• pp.46-56
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• 2012

The purpose of virtual metrology (VM) in semiconductor manufacturing is to predict every wafer's metrological values based on its process equipment data without an actual metrology. In this paper, we propose novelty detection-based reliability estimation models for VM in order to support flexible utilization of VM results. Because the proposed model can not only estimate the reliability of VM, but also identify suspicious process variables lowering the reliability, quality control actions can be taken selectively based on the reliance level and its causes. Based on the preliminary experimental results with actual semiconductor manufacturing process data, our models can successfully give a high reliance level to the wafers with small prediction errors and a low reliance level to the wafers with large prediction errors. In addition, our proposed model can give more detailed information by identifying the critical process variables and their relative impacts on the low reliability.

• 한국경영과학회지
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• 제30권4호
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• pp.15-25
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• 2005

As implied by the terms of IT productivity Paradox, measuring the Information technology contribution to economic performance has been one of the challenging issues to both policy makers and business professionals. As such, diverse attempts with sophisticate analyses have been reported in the literature to analyze the effect of IT contributions. In this paper, we follow Growth Accounting Method to measure the IT contribution effect to manufacturing firm's economic performance in Korea. Various regression methods and statistical analyses are applied with fourteen years of industry Panel data. Using the Cobb-Douglas function, time lag analysis is made to understand IT effect to economic growth. Instead of capturing data from individual firm, industry level data from the National Statistics Bureau is used for IT capital, non-IT capital, and so on. Statistical analysis following the panel unit test and Panel co-integration test was performed to reveal the exact effect of IT contribution to economic performance. Empirical testing results for non-stationary nature of IT investment effect are reported as well as IT contribution to manufacturing industry's economic performance.

• 보건교육건강증진학회지
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• 제21권3호
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• pp.35-51
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• 2004

The purpose of this study was to identify the health promotion behavior(HPB) of the labor workers at the cement manufacturing company based on the Health Promotion Model by Pender(1996). Data were collected by self-reported questionnaire from 180 blue workers at the 2 cement factories under the permission of data collection and cooperation with managers in the factories. For data analysis, Descriptive statistics, t-test, ANOVA, Pearson correlation, Multiple regression with SPSS/PC + 10.0 version were used. The results were as follows: 1. The average scores for the HPB, consisted of 6 subdimensions was 2.74. The highest mean score was 2.88 in 'Exercise' and the lowest on was 2.58 'Responsibility of health'. 2. The score of the HPB was statistically different according to educational level(p<.00l), perceived health status(p<.00l) and satisfaction of working environment(p<.05). 3. HPB was positively related to age(p<.05), perceived health status(p<.00l), job satisfaction(p<.05), and satisfaction of working environment(p<.05), while it showed negative correlation with educational level(p<.01). 4. According to the results of multiple regression analysis, factors affecting HPB were perceived health status and education level explained 20.3% of variance. From this research findings, we need to different approach in develop health promotion program of Cement manufacturing company workers and focusing on improvement to job satisfaction and satisfaction of working environment.

• 대한안전경영과학회지
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• 제6권3호
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• 한국CDE학회논문집
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• 제14권6호
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• pp.415-423
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• 2009

Because of the fast changing car design and increasing facilities, manufacturing process of cars is getting more complex now a days. Particularly, car manufacturing system that consist of automated devices, applies various simulation techniques to validate device motion and detect collision. To cope with this problem, traditional manufacturing system deployed test-run with the real devices. However, increased computing power in a contemporary manufacturing system changes it into realistic 3D simulation environment. Similarly, managed device data that was generated using 2D traditionally, can be converted to 3D realistic simulation. The existing problem with 3D simulation is disjoint data interaction between different work stations. Consequently, JIGs, fixing the car part accurately, are changed according to fixing position on the part or a part shape properties. In practice, the 3D JIG data has to be managed according to kinematic information, but not of its features. However, generating kinematic information to the 3D model repeatedly according to frequent change in part is not explained in current literatures. To fill this knowledge gap, this paper suggests an improving method of rendering 3D JIG kinematics information to simulation model. Thereafter, it shows the result of implementation.

• International Journal of Safety
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• 제5권1호
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• pp.37-41
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• 2006

The major objective of the statistical analysis about industrial accidents is to determine the safety factors so that it is possible to prevent or decrease the number of future accidents by educating those who work in a given industrial field in safety management. So far, however, there exists no quantitative method for evaluating danger related to industrial accidents. Therefore, as a method for developing quantitative evaluation technique, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze features of industrial accidents, a retrospective analysis was performed on 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work was chosen from data related to manufacturing businesses during a three-year period ($2002{\sim}2004$) in Korea. This study used AnswerTree of SPSS and the analysis results enabled us to determine the most important variables that can affect injured people such as the occurrence type, the company size, and the time of occurrence. Also, it was found that the classification system adopted in the present study using QUEST algorithm is quite reliable.

• 한국시뮬레이션학회논문지
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• 제19권4호
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• pp.21-29
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• 2010

본 연구는 시뮬레이션 방법을 이용한 자동차용 열 수축 튜브 생산 공정을 가상의 생산 공정 모델로 구현하고, 구현된 모델을 기반으로 열 수축 튜브 생산 공정을 분석하는 연구이다. 자동차용 열 수축 튜브 생산 공정을 분석하기 위해서 공정별로 생성되는 데이터를 수집하고, 수집된 데이터 분석을 통한 자동차용 열 수축 튜브 생산 공정을 분석할 수 있는 가상의 생산 공정 모델을 구현하였다. 구현된 모델을 통해 공정 내에서 발생되는 병목현상 파악 및 원인분석, 공정별 사이클 타임, 부품 생산량 등을 산정함으로써 현 공정 분석 및 개선방안을 모색할 수 있어 기업의 생산 공정관리 효율성을 높일 수 있다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.204-206
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• 2022

스마트 팩토리(Smart Factory) 고도화의 핵심으로 평가되는 디지털 트윈(Digital Twin)은 현실 세계의 자산과 동일한 속성 및 기능을 가지는 디지털 복제본을 가상의 세계에 구현하는 기술이다. 디지털 트윈 기술이 적용된 스마트팩토리는 생산공정의 실시간 모니터링, 생산공정 시뮬레이션, 생산설비 예지보전 등의 서비스를 지원할 수 있어 생산비용 절감 및 생산성 향상에 기여할 것으로 기대된다. AAS(Asset Administration Shell)는 디지털 트윈을 구현하기 위한 필수 기술로, 현실의 물리적 자산을 디지털로 표현하는 방법을 제공한다. 본 논문에서는 스마트팩토리 내 생산설비를 자산으로 간주하여, 운용 중인 실시간 CNC(Computer Numerical Control) 모니터링 시스템에서 활용할 제조 데이터 수집을 위한 AAS를 설계하였다.