• 제목/요약/키워드: Cellular manufacturing

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The Effects of Product, Process, and Facilities Characteristics on the Conversion Processes and Outcomes for Cellular Manufacturing : An Empirical Study

  • Choi, Moo-Jin;Jun, Minjoon
    • 경영과학
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    • 제12권2호
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    • pp.165-188
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    • 1995
  • The conversion processes from traditional job shops to cellular manufacturing systems can be viewed as an aggregation of cause-and-effect relationships among many strategic, managerial, and technical variables. Therefore, management needs to fully understand these interacting variables and possible relationships between the variables to successfully convert their plants to cellular manufacturing systems. The purpose of this study is to assist such management's needs in part. The objectives of this research are i) investigating contingency variables that may affect the conversion processes and outcomes to cellular manufacturing systems and ii) examining relationships between the variables and the conversion processes and outcomes. In this paper, particularly three categories of variables are examined: product, process routing, and process technology / facilities characteristics. Literature review and the mail survey method are used. The results are compared and synthesized with the findings of previous studies for useful discussions. Some previous arguments and propositions are empirically supported.

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셀 구성을 위한 그룹유전자 알고리듬의 변형들에 대한 연구 (A study on the variations of a grouping genetic algorithm for cell formation)

  • 이종윤;박양병
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2003년도 추계학술대회 및 정기총회
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    • pp.259-262
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    • 2003
  • Group technology(GT) is a manufacturing philosophy which identifies and exploits the similarity of parts and processes in design and manufacturing. A specific application of GT is cellular manufacturing. the first step in the preliminary stage of cellular manufacturing system design is cell formation, generally known as a machine-part cell formation(MPCF). This paper presents and tests a grouping gentic algorithm(GGA) for solving the MPCF problem and uses the measurements of e(ficacy. GGA's replacement heuristic used similarity coefficients is presented.

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유전 알고리즘을 이용한 셀 배치방법에 관한 연구 (A Facility Layout Planning Method in Cellular Manufacturing Environment Using Genetic Algorithm)

  • 정승환;강무진
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 추계학술대회 논문집
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    • pp.334-338
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    • 2000
  • One of the major drawbacks of the existing facility layout methods is that most of them were developed based on pre-defined cost functions, and therefore fail to cope with the dynamic aspects of modern manufacturing systems. Another drawback is that due to the poor representation capability of the block diagrams, they are not able to convey the sufficient information needed by facility designers. In this paper, a system for solving facility layout problem considering these matters in cellular manufacturing environment is proposed and implemented using GA approach with embedded simulation module and virtual reality technologies.

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Cellular manufacturing system design with proper assignment of machines and parts

  • 원유경
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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    • pp.390-396
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    • 2002
  • This study is concerned with the strict machine-cell and part-family grouping (MCPFG) in cellular manufacturing system design. Most of MCPFG methodologies often suffer from improper assignment of machines and parts in which exceptional machine has more common operations with machines in a cell other than its own cell and exceptional part has more operations through machines in a cell other than the cell corresponding to its own family. This results in the loss of similarity in part design or common setup of machines and the benefits from the conversion of job shop manufacturing into cellular manufacturing are lost. In this study, a two-phase methodology is proposed to find the machine-cells and part families under the strict constraints in which all machines and parts are assigned to its most proper cells and families. Test results with moderately medium-sized ill-structured MCPFG problems available from the literature show the substantial efficiency of the proposed approach.

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유전 알고리즘에 기초한 셀 배치의 설계 (Design of Cellular Layout based on Genetic Algorithm)

  • 이병욱;조규갑
    • 한국정밀공학회지
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    • 제16권6호
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    • pp.197-208
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    • 1999
  • This paper presents an operation sequence-based approach for determining machine cell layout in a cellular manufacturing environment. The proposed model considers the sequence of operations in evaluating the intercell and intracell movements. In this paper, design of cellular layout has an objective of minimization of total material flow among facilities, where the total material flow is defined as a weighted sum of both intercell and intracell part movements. The proposed algorithm is developed by using genetic algorithm and can be used to design an optimal cellular layout which can cope with changes of shop floor situation by considering constraints such as the number of machine cells and the number of machines in a machine cell.

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신경망을 이용한 제조셀 형성 알고리듬 (A Manufacturing Cell Formantion Algorithm Using Neural Networks)

  • 이준한;김양렬
    • 경영과학
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    • 제16권1호
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    • pp.157-171
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    • 1999
  • In a increasingly competitive marketplace, the manufacturing companies have no choice but looking for ways to improve productivity to sustain their competitiveness and survive in the industry. Recently cellular manufacturing has been under discussion as an option to be easily implemented without burdensome capital investment. The objective of cellular manufacturing is to realize many aspects of efficiencies associated with mass production in the less repetitive job-shop production systems. The very first step for cellular manufacturing is to group the sets of parts having similar processing requirements into part families, and the equipment needed to process a particular part family into machine cells. The underlying problem to determine the part and machine assignments to each manufacturing cell is called the cell formation. The purpose of this study is to develop a clustering algorithm based on the neural network approach which overcomes the drawbacks of ART1 algorithm for cell formation problems. In this paper, a generalized learning vector quantization(GLVQ) algorithm was devised in order to transform a 0/1 part-machine assignment matrix into the matrix with diagonal blocks in such a way to increase clustering performance. Furthermore, an assignment problem model and a rearrangement procedure has been embedded to increase efficiency. The performance of the proposed algorithm has been evaluated using data sets adopted by prior studies on cell formation. The proposed algorithm dominates almost all the cell formation reported so far, based on the grouping index($\alpha$ = 0.2). Among 27 cell formation problems investigated, the result by the proposed algorithm was superior in 11, equal 15, and inferior only in 1.

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The Effects of the Scope of Plant Layout Conversion on Manufacturing Cell Design Processes and Outcomes

  • Choi, Moon-Jin
    • 한국경영과학회지
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    • 제18권3호
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    • pp.159-177
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    • 1993
  • One of major research issues in cellular manufacturing is studing factors that are fovorable or detrimental to the conversion of traditional functional layouts to GT cellular layouts. Among many factors, this paper explored plausible relationships between the scope of plant conversion and the manufacturing cell design processes and outcomes. The cell design practices of 28 U. S. plants were surveyed through a mail questionaire. While most relationships were not statistically significant, some interesting findings and insights could be drawn. With this researhc, we can better understand a part of relationships between the company's conversion strategy and the cell design strategies and outcomes.

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셀형유연조립시스템에서의 네트웍형 셀배치 (Network-type Cell Layout in Cellular Flexible Assembly Systems)

  • 노인규;최형호
    • 산업경영시스템학회지
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    • 제19권39호
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    • pp.63-73
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    • 1996
  • With the success of flexible manufacturing systems (FMSs), flexible assembly systems (FASs) have been developed to automate factories further. As in a cellular FMS, a cellular FAS is considered as the most flexible and feasible assembly system configuration Because of the differences between manufacturing and assembly operation, the logic of cell formation and cell layout between a FMS and a FAS is not the same. Since the time for assembly operation is usually relatively short, the transfer time is thus very crucial for the performance of assembly systems. Therefore in assembly systems it is important to reduce the transfer time by sequencing operations efficiently and arranging machines like the sequences. The network-type layout is not only feasible for the machine arrangement based on operation sequences, but it has also layout flexibility. Therefore it is a reasonable layout configuration for cellular FASs. This paper presents a method for the cell layout based on the network-type layout in a cellular FAS design.

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다 속성분석방법을 이용한 제조물류시스템의 성능산정모델 (A Material Handling Performance Evaluation Model for Cellular Manufacturing System of Based on Multi-Attributes Analysis Method)

  • 황홍석
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2000년도 추계학술대회 및 정기총회
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    • pp.167-170
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    • 2000
  • This paper is concerned with development of a performance evaluation model for material handling system in cellular manufacturing system based on multi-attributes analysis method. We used the AHP(analytic hierarchy process) and fuzzy set ranking methodologies to overcome the special decision problems; those of multi -objective, multi-criterion, and multi-attributes. We proposed a 3-step approaches and we developed a systemic and practical computer program to solve the problems in the proposed methods. Computational experiments are then performed to cellular manufacturing system and show the effectiveness of the proposed model.

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셀 생산방식에서 자기조직화 신경망과 K-Means 알고리즘을 이용한 기계-부품 그룹형성 (Machine-Part Grouping in Cellular Manufacturing Systems Using a Self-Organizing Neural Networks and K-Means Algorithm)

  • 이상섭;이종섭;강맹규
    • 산업경영시스템학회지
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    • 제23권61호
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    • pp.137-146
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    • 2000
  • One of the problems faced in implementing cellular manufacturing systems is machine-part group formation. This paper proposes machine-part grouping algorithms based on Self-Organizing Map(SOM) neural networks and K-Means algorithm in cellular manufacturing systems. Although the SOM spreads out input vectors to output vectors in the order of similarity, it does not always find the optimal solution. We rearrange the input vectors using SOM and determine the number of groups. In order to find the number of groups and grouping efficacy, we iterate K-Means algorithm changing k until we cannot obtain better solution. The results of using the proposed approach are compared to the best solutions reported in literature. The computational results show that the proposed approach provides a powerful means of solving the machine-part grouping problem. The proposed algorithm Is applied by simple calculation, so it can be for designer to change production constraints.

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