• 제목/요약/키워드: Manufacturing Analysis

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IT 기업의 R&D 투자 및 운영 효율성 분석 : 서비스업 및 제조업의 비교를 중심으로 (R&D Investment and Operational Efficiency Analysis of IT Firms : Comparative Analysis of Service and Manufacturing Sectors)

  • 김창희;이규석;김수욱
    • 한국IT서비스학회지
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    • 제15권2호
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    • pp.51-63
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    • 2016
  • In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

데이터 정제와 그래프 분석을 이용한 대용량 공정데이터 분석 방법 (An Analysis Method of Superlarge Manufacturing Process Data Using Data Cleaning and Graphical Analysis)

  • 박재홍;변재현
    • 품질경영학회지
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    • 제30권2호
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    • pp.72-85
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    • 2002
  • Advances in computer and sensor technology have made it possible to obtain superlarge manufacturing process data in real time, letting us extract meaningful information from these superlarge data sets. We propose a systematic data analysis procedure which field engineers can apply easily to manufacture quality products. The procedure consists of data cleaning and data analysis stages. Data cleaning stage is to construct a database suitable for statistical analysis from the original superlarge manufacturing process data. In the data analysis stage, we suggest a graphical easy-to-implement approach to extract practical information from the cleaned database. This study will help manufacturing companies to achieve six sigma quality.

Structural Framework to Measure Smart Technology Capability for Smart Factory of Manufacturing Fields

  • CHUI, YOUNG YOON
    • 한국경영공학회지
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    • 제23권4호
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    • pp.165-177
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    • 2018
  • Smart technology has been utilized in various fields of all kinds of industries. Manufacturing industry has built its smart technology environment appropriate for its manufacturing fields in order to strengthen its manufacturing performance and competitiveness. The advance of smart technology for manufacturing industry needs to efficiently produce products, and response customer's demands and services in a global industrial environment. The smart technology capability of manufacturing fields is very crucial for the innovative production and efficient operation activities, and for efficient advancement of the manufacturing performance. We have necessitated a scientific and objective method that can gauge a smart technology ability in order to manage and strengthen the smart technology ability of manufacturing fields. This research provides a comprehensive framework that can rationally gauge the smart technology capability of manufacturing fields for effectively managing and advancing their smart technology capabilities. In this research, we especially develop a structural framework that can gauge the smart technology capability for a smart factory of manufacturing fields, with verifying by reliability analysis and factor analysis based on previous literature. This study presents a 13-item framework that can measure the smart technology capability for a smart factory of manufacturing fields in a smart technology perspective.

UML을 이용한 컴포넌트 기반의 DFM을 위한 제조정보 시스템의 개발 (- A Component-Based Manufacturing Information Systems for DFM Using UML -)

  • 김진대;이홍희
    • 대한안전경영과학회지
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    • 제5권2호
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    • pp.75-85
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    • 2003
  • Manufacturing firms have adapted seriously the Design for Manufacture and Assembly (DFMA) techniques which consider concurrently all factors related to the product development by using effective communications and sharing of information on product development processes. This study performed modelling and characterizing the data related to product manufacturing information for Design for Manufacture(DFM) evaluation and analysis. It adapted component-based development method for communicating and managing manufacturing information among distributed manufacturing organizations. Introducing component-based development offers safety and speed to network based system. This development using Unified Modelling Language(UML) provides efficient way for reconstruction and distribution of applications. Also, the integration of database and component into the internet environment enables to communicate and manage effectively manufacturing information for DFM evaluation and analysis at any place in the world. Therefore this system can make it more reasonable that evaluating, analyzing, and effective decision making of product design using DFM technique.

자동차 PANEL 성형 CAE 적용 사례 연구 및 금형제작 PROCESS의 개선 (A STUDY ON CAE APPLICATION FOR FORMING(STAMPING) OF AUTOMOTIVE PANEL AND IMPROVEMENT OF DIE MANUFATURING PROCESS)

  • 박용국;김재훈;곽태수
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 1998년도 제2회 박판성형심포지엄 논문집 박판성형기술의 현재와 미래
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    • pp.33-40
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    • 1998
  • In recent domestic automotive industry, applications of computer simulation to the manufacturing of stamping dies for inner and outer body panels which greatly affect durability and aesthetic quality of automobiles, have been increased. Enhancement of die quality, and reduction of total die manufacturing time and consequently manufacturing cost are the visible outcome. However, to successfully apply the result of simulation by a commercial package to the die manufacturing, development of an optimal die manufacturing process is required upon the completion of analysis of forte and shortcomings of available sheet metal forming softwares in the market. Based on the results of numerical analysis of front door outer panel forming, this paper evaluates the applicability of simulation results to the real die making for automotive body panels. Also, it attempts to select an optimal die manufacturing process including design, machining and tryout. Lastly, it discusses the expected effects by adopting the selected process in a real stamping die manufacturing facility.

SOI웨이퍼의 마이크로가속도계 센서에 대한 열변형 유한요소해석 (Finite Element Analysis of Thermal Deformations for Microaccelerometer Sensors using SOI Wafers)

  • 김옥삼;구본권;김일수;김인권;박우철
    • 한국공작기계학회논문집
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    • 제11권4호
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    • pp.12-18
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    • 2002
  • Silicon on insulator(SOI) wafer is used in a variety of microsensor applications in which thermal deformations and other mechanical effects may dominate device Performance. One of major Problems associated with the manufacturing Processes of the microaccelerometer based on the tunneling current concept is thermal deformations and thermal stresses. This paper deals with finite element analysis(FEA) of residual thermal deformations causing popping up, which are induced in micrormaching processes of a microaccelerometer. The reason for this Popping up phenomenon in manufacturing processes of microaccelerometer may be the bending of the whole wafer or it may come from the way the underetching occurs. We want to seek after the real cause of this popping up phenomenon and diminish this by changing manufacturing processes of mic개accelerometer. In microaccelerometer manufacturing process, this paper intend to find thermal deformation change of the temperature distribution by tunnel gap and additional beams. The thermal behaviors analysis intend to use ANSYS V5.5.3.

CCA를 통한 반도체 공정 변인들의 상관성 분석 : 웨이퍼검사공정의 전압과 불량결점수와의 관계를 중심으로 (Correlation Analysis on Semiconductor Process Variables Using CCA(Canonical Correlation Analysis) : Focusing on the Relationship between the Voltage Variables and Fail Bit Counts through the Wafer Process)

  • 김승민;백준걸
    • 대한산업공학회지
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    • 제41권6호
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    • pp.579-587
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    • 2015
  • Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.

제조 빅데이터 시스템을 위한 효과적인 시각화 기법 (Effective visualization methods for a manufacturing big data system)

  • 류관희
    • Journal of the Korean Data and Information Science Society
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    • 제28권6호
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    • pp.1301-1311
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    • 2017
  • 제조 빅데이터 시스템은 제조 전 공정에서 관련된 4M 데이터의 수집, 저장, 관리, 예측적 분석을 통해 선제적 제조 활동 개선이 가능한 의사결정을 지원하고 있다. 이러한 시스템에서 데이터의 효율적인 관리와 운영을 위해 데이터를 효과적으로 시각화하는 것이 무엇보다도 중요하다. 본 논문에서는 제조 빅데이터 시스템에서 데이터 수집, 분석 및 예측 결과를 효과적으로 보여 주기 위해 사용가능한 시각화 기법을 제시한다. 본 논문에서 제시된 시각화 기법을 통해 제조 현장에서 발생하는 문제를 보다 손쉽게 파악할 수 있었을 뿐만 아니라 이들 문제를 효과적으로 대응할 수 있어 매우 유용하게 사용될 수 있음을 확인하였다.

6 시그마 위한 대용량 공정데이터 분석에 관한 연구 (A Study on Analysis of Superlarge Manufacturing Process Data for Six Sigma)

  • 박재홍;변재현
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2001년도 추계학술대회 논문집
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    • pp.411-415
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    • 2001
  • Advances in computer and sensor technology have made it possible to obtain superlarge manufacturing process data in real time, letting us to extract meaningful information from these superlarge data sets. We propose a systematic data analysis procedure which field engineers can apply easily to manufacture quality products. The procedure consists of data cleaning and data analysis stages. Data cleaning stage is to construct a database suitable for statistical analysis from the original superlarge manufacturing process data. In the data analysis stage, we suggest a graphical easy-to-implement approach to extract practical information from the cleaned database. This study will help manufacturing companies to achieve six sigma quality.

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제조 셀 구현을 위한 군집분석 기반 방법론 (Cluster Analysis-based Approach for Manufacturing Cell Formation)

  • 심영학;황정윤
    • 산업경영시스템학회지
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    • 제36권1호
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    • pp.24-35
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    • 2013
  • A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.