• 제목/요약/키워드: Classification and Coding System

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Fuzzy 밀집기법을 이용한 맞춤형 부픔 분류법의 개발 (Development of a Company-Tailored Part Classification & Coding System Using fuzzy clustering Techniques)

  • 박진우
    • 한국경영과학회지
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    • 제13권1호
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    • pp.31-38
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    • 1988
  • This paper presents a methodology for the development of a part classification and coding system suited to each individual company. When coding a group of parts for a specific company by a general purpose part classification & coding system like OPITZ system, it is frequently observed that we use only a small subset of total available code numbers. Such sparsity in the actual occurrences of code numbers implies that we can design a better system which uses digits of the system more parsimoniously. A 2-dimensional fuzzy ISODATA algorithm is developed to extract the important characteristics for the classification from the set of given parts. Based on the extracted characteristics nd the distances between fuzzy clustering cenetroids, a company-unique classification and coding system can be developed. An example case study for a medium sized machine shop is presented.

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분류 및 코딩시스템을 이용한 디지털 가상공장 객체의 효율적 관리 (The Efficient Management of Digital Virtual Factory Objects Using Classification and Coding System)

  • 김유석;강형석;노상도
    • 한국CDE학회논문집
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    • 제12권5호
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    • pp.382-394
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    • 2007
  • Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

수주생산에서의 설계정보 관리를 위한 부품분류와 코딩 (A Classification and Coding System for the Design Information Management in Make-to-Order Manufacturing)

  • 이규용;김재균;문치웅
    • 산업경영시스템학회지
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    • 제22권50호
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    • pp.195-207
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    • 1999
  • Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing. The steps of developing the C&C system are as follows: 1) analysis of existing coding system and drawing type; 2) design of C&C system; 3) practice of designed coding system to a field.

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정보검색 기법을 이용한 산업/직업 코드 자동 분류 시스템 (An automated Classification System of Standard Industry and Occupation Codes by Using Information Retrieval Techniques)

  • 임희석
    • 컴퓨터교육학회논문지
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    • 제7권4호
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    • pp.51-60
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    • 2004
  • 본 논문은 통계청에서 실시하는 인구 주택 총조사와 사업체 기초통계조사 시 실시되는 수작업에 의한 표준 산업/직업 코드 분류 시 발생하는 막대한 비용과 시간, 일관성의 결여 등을 해소하기 위한 표준 산업/직업 코드 자동 분류 시스템을 제안한다. 제안한 시스템은 정보 검색 기법과 문서 분류 기법을 이용하여 자연어로 기술된 레코드를 입력 받아 입력 레코드에 해당하는 분류 코드를 생성한다. 수작업으로 올바른 코드가 할당되어 있는 산업 분류 레코드 46,762개와 직업 분류 코드 36,286개를 이용하여 10-fold cross-validation evaluation을 수행한 결과, 제안한 시스템은 완전 자동 모드에서 2수준의 산업 분류에 대해서 87.08%, 5수준에 대해서는 66.08%의 생성률을 보였으며 반자동 모드에서는 각각 99.10%와 92.88%의 성능을 보였다. 직업 분류 코드에 대한 성능은 산업 분류 코드에 대한 성능보다는 약간 저하된 성능을 보였다. 제안한 시스템은 아직 수작업을 완전히 대체할 수 있는 완전 자동 분류기로서는 많은 개선의 여지를 가지고 있지만 수작업을 최소화할 수 있는 반자동 도구나 수작업의 정확도를 검증할 수 있는 보조 도구로써 충분히 활용될 수 있을 것으로 기대된다.

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인간시각 체계를 이용한 적응 구획 절단 부호화 (An Adaptive Block Truncation Coding Using Human Visual System)

  • 신용달;이봉락;이건일
    • 전자공학회논문지B
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    • 제30B권12호
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    • pp.67-72
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    • 1993
  • An adaptive block truncation coding(BTC) using human visual system(HVS) is proposed. To reduce visible blocking effect at sensitive area in HVS. a new category classification coefficient is proposed. The categroy classification coefficient was derived by combining the modified HVS and standard deviation. By computer simulations, we showed that the proposed method reduced blocking effect at low bit rate coding more than the conventional Hui's method.

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예제기반 한국어 표준 산업/직업 코드 분류 (An Example-based Korean Standard Industrial and Occupational Code Classification)

  • 임희석
    • 한국산학기술학회논문지
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    • 제7권4호
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    • pp.594-601
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    • 2006
  • 통계청에서 실시하는 통계 조사에는 한국 표준 산업/직업 분류 코드를 작성하는 작업이 많이 포함되는데, 현재 대부분의 코드 분류 작업은 수작업으로 이루어지고 있으며, 이로 인하여 막대한 노동력과 비용이 소모되고 작업결과의 일관성을 유지하기 어렵다는 문제점이 있다. 본 논문은 수동 코드 분류 규칙과 예제기반의 자동 학습을 이용하는 한국어 표준 산업/직업 코드 자동 분류 시스템을 제안한다. 제안된 시스템은 산업과 직업에 대하여 설명하는 자 연어를 입력받아 해당 산업/직업 분류 코드를 생성하는 시스템으로 수작업으로 구축된 규칙을 적용한 후 규칙이 적용되지 않는 레코드는 예제 기반의 학습을 이용한 자동 분류 시스템에 의해서 해당 코드를 할당한다. 수작업 규칙 260여개와 40만여개의 예제를 이용하여 학습한 시스템에 대하여 실험한 결과 제안한 시스템은 직업 코드 분류에서 76.69% 그리고 산업 코드 분류에서는 99.68%의 정확도를 보였다.

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Adaptive Transform Image Coding by Fuzzy Subimage Classification

  • Kong, Seong-Gon
    • 한국지능시스템학회논문지
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    • 제2권2호
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    • pp.42-60
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    • 1992
  • An adaptive fuzzy system can efficiently classify subimages into four categories according to image activity level for image data compression. The system estimates fuzzy rules by clustering input-output data generated from a given adaptive transform image coding process. The system encodes different images without modification and reduces side information when encoding multiple images. In the second part, a fuzzy system estimates optimal bit maps for the four subimage classes in noisy channels assuming a Gauss-Markov image model. The fuzzy systems respectively estimate the sampled subimage classification and the bit-allocation processes without a mathematical model of how outputs depend on inputs and without rules articulated by experts.

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전문가 시스템을 이용한 부품 분류 및 코딩 (an Expert System for Part Classification and Coding)

  • 박양병
    • 대한산업공학회지
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    • 제17권2호
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    • pp.17-26
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    • 1991
  • This paper discusses an expert system to generate part codes and construct part families, ESPCC, for the group technology application. The ESPCC, that is developed by using VP-Expert rule-based expert system development tool, embodies the specific knowledge of human experts to determine part codes consistent with the OPITZ classification and coding system. The ESPCC is implemented on an IBM compatible personal computers running MS-DOS.

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수주생산에서의 설계정보 관리를 위한 부품분류와 코딩 (A Classification and Coding System for the Design Information Management in Make-to-Order Manufacturing)

  • 이규용;김재균;문치웅
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1998년도 추계학술대회 논문집
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    • pp.166-170
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    • 1998
  • Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing.

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퍼지시스템에 의한 부영상의 적응분류와 영상데이타 압축에의 적용 (Adaptive Classification of Subimages by the Fuzzy System for Image Data Compression)

  • Kong, Seong-Gon
    • 대한전기학회논문지
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    • 제43권7호
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    • pp.1193-1205
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    • 1994
  • This paper presents a fuzzy system that adaptively classifies subimages to four classes according to image activity distribution. In adaptive transform image coding, subimage classification improves the compression performance by assigning different bit maps to different classes. A conventional classification method sorts subimages by their AC energy and divides them to classes with equal number of subimages. The fuzzy system provides more flexible classification to natural images with various distribution of image details than does the conventional method. Clustering of training data in the input-output product space generated the fuzzy rules for subimage classification. The fuzzy system of small number of fuzzy rules successfully classified subimages to improve the compression performance of the transform image coding without sorting of AC energies.