• Title, Summary, Keyword: Cell grouping

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

  • Shim, Young Hak;Hwang, Jung Yoon
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.36 no.1
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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.

Genetic Algorithm for Designing Independent Manufacturing Cells (독립적인 생산셀 설계를 위한 유전 알고리즘)

  • Moon, Chi-Ung;Yi, Sang-Yong
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.3
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    • pp.581-595
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    • 1997
  • The procedure of grouping the machines and parts to form cells is called manufacturing cell design. The manufacturing cell design is an important step in the development and implementation of advanced manufacturing systems. For the successful implementation of the manufacturing systems, identification of independent manufacturing cells, i.e., cells where parts are completely processed in the cell and no intercell movements, is necessary in the design phase. In this paper, we developed a mixed integer programming model and genetic algorithm based procedure to solve the independent manufacturing cells design problem considering the alternative process plans and machines duplication. Several manufacturing parameters such as, production volume, machine capacity, processing time, number of cells and cell size, are considered in the process. The model determines the process plan for parts, port families and machine cells simultaneously. The model has been verified with the numerical examples.

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

  • 이준한;김양렬
    • Korean Management Science Review
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    • v.16 no.1
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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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A Symbolic Layout Generator for CMOS Standard Cells Using Artificial Intelligence Approach (인공지능 기법을 이용한 CMOS 표준셀의 심볼릭 레이아웃 발생기)

  • 유종근;이문기
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.6
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    • pp.1080-1086
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    • 1987
  • SLAGEN, a system for symbolic cell layout based on artificial intelligence approach, takes as input a transistor connection description of CMOS standard cells and environment information, and outputs a symbolic layout description. SLAGEN performas transistor grouping by a heuristic search method, in order to minimize the number of separations, and then performs group reordering and transistor reordering with an eye toward minimizing routing. Next, SLAGEN creates a rough initial routing in order to guarantee functionality and correctness, and then improve the initial routing by a rule-based approach.

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A heuristic algorithm for forming machine cells and part families in group technology (그룹 테크놀러지에서의 기계 및 부품군을 형성하기 위한 발견적 해법)

  • Ree, Paek
    • Journal of Korean Institute of Industrial Engineers
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    • v.22 no.4
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    • pp.705-718
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    • 1996
  • A similarity coefficient based algorithm is proposed to solve the machine cells and part families formation problem in group technology. Similarity coefficients are newly designed from the machine-part incidence matrix. Machine cells are formed using a recurrent neural network in which the similarity coefficients are used as connection weights between processing units. Then parts are assigned to complete the cell composition. The proposed algorithm is applied to 30 different kinds of problems appeared in the literature. The results are compared to those by the GRAFICS algorithm in terms of the grouping efficiency and efficacy.

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Cell Formation Considering the Minimization of Manufacturing Leadtime in Cellular Manufacturing Systems (셀룰러 생산시스템에서 생산 리드타임의 최소화를 고려한 셀 구성 방법)

  • Yim, Dong-Soon;Woo, Hoon-Shik
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.4
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    • pp.285-293
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    • 2004
  • In this study, a machine grouping problem for the formation of manufacturing cells is considered. We constructed the problem as minimizing manufacturing leadtime consisting of parts' processing, moving, and waiting time. Specifically, the main objective of the defined problem is established as minimizing inter-cell traffic in order to minimize the part's moving time. In addition, to reduce the waiting time of parts, the load balance among cells is implicitly included as constraints. Since this problem is well known as NP-complete and cannot be solved in polynomial time, a genetic algorithm is implemented to obtain solutions. Also, a local optimization algorithm is applied in order to improve the solution by the genetic algorithm. Several experiments show that the suggested algorithms guarantee near optimal solutions in a few seconds.

An Efficient Test Compression Scheme based on LFSR Reseeding (효율적인 LFSR 리시딩 기반의 테스트 압축 기법)

  • Kim, Hong-Sik;Kim, Hyun-Jin;Ahn, Jin-Ho;Kang, Sung-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.3
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    • pp.26-31
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    • 2009
  • A new LFSR based test compression scheme is proposed by reducing the maximum number of specified bits in the test cube set, smax, virtually. The performance of a conventional LFSR reseeding scheme highly depends on smax. In this paper, by using different clock frequencies between an LFSR and scan chains, and grouping the scan cells, we could reduce smax virtually. H the clock frequency which is slower than the clock frequency for the scan chain by n times is used for LFSR, successive n scan cells are filled with the same data; such that the number of specified bits can be reduced with an efficient grouping of scan cells. Since the efficiency of the proposed scheme depends on the grouping mechanism, a new graph-based scan cell grouping heuristic has been proposed. The simulation results on the largest ISCAS 89 benchmark circuit show that the proposed scheme requires less memory storage with significantly smaller area overhead compared to the previous test compression schemes.

An Algorithm for Minimizing Exceptional Elements Considering Machine Duplication Cost and Space Constraint in Cellular Manufacturing System (기계중복비용과 공간제약을 고려한 예외적 요소의 최소화 알고리듬)

  • Chang, Ik;Chung, Byung-hee
    • IE interfaces
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    • v.12 no.1
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    • pp.10-18
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    • 1999
  • Job shop manufacturing environments are using the concept of cellular manufacturing systems(CMS) which has several advantages in reducing production lead times, setup times, work-in-process, etc. Utilizing the similarities between cell-machine, part-machine, and the shape/size of parts, CMS can group machines and parts resulting in improved efficiency of this system. However, when grouping machines and parts in machine cells, there inevitably occurs exceptional elements(EEs), which can not operate in the same machine cell. Minimizing these EEs in CMS is a critical point that improving production efficiency. Constraints in machine duplication cost, machining process technology, machining capability, and factory space limitations are main problems that prevent achiving the goal of maintaining an ideal CMS environment. This paper presents an algorithm that minimizes EEs under the constraints of machine duplication cost and factory space limitation. Developing exceptional operation similarity(EOS) by cell-machine incidence matrix and part-machine incidence matrix, it brings the machine cells that operate the parts or not. A mathematical model to minimize machine duplication is developed by EOS, followed by a heuristic algorithm in order to reflect dynamic situation resulting from minimizing exceptional elements process and the mathematical model. A numerical example is provided to illustrate the algorithm.

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Application of Spatial Analysis Modeling to Evaluating Functional Suitability of Forest Lands against Land Slide Hazards (공간분석(空間分析)모델링에 의한 산지(山地)의 토사붕괴방재기능(土砂崩壞防災機能) 적합도(適合度) 평가(評價))

  • Chung, Joosang;Kim, Hyungho;Cha, Jaemin
    • Journal of Korean Society of Forest Science
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    • v.90 no.4
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    • pp.535-542
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    • 2001
  • The objective of this study is to develop a spatial analysis modeling technique to evaluate the functional suitability of forest lands for land slide prevention. The functional suitability is classified into 3 categories of high, medium and low according to the potential of land slide on forest lands. The potential of land slide hazards is estimated using the measurements of 7 major site factors : slope, bed rock, soil depth, shape of slope, forest type and D.B.H. class of trees. The analytic hierarchical process is applied to determining the relative weight of site factors in estimating the potential of land slides. The spatial analysis modeling starts building base layers for the 7 major site factors by $25m{\times}25m$ grid analysis or TIN analysis, reclassifies them and produces new layers containing standardized attribute values, needed in estimating land slide potential. To these attributes, applied is the weight for the corresponding site factor to build the suitability classification map by map algebra analysis. Then, finally, cell-grouping operations convert the suitability classification map to the land unit function map. The whole procedures of the spatial analysis modeling are presented in this paper.

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Identification and Distribution of Bacillus Species in Doenjang by Whole-Cell Protein Patterns and 16S rRNA Gene Sequence Analysis

  • Kim, Tae-Woon;Kim, Young-Hoon;Kim, Sung-Eon;Lee, Jun-Hwa;Park, Cheon-Seok;Kim, Hae-Yeong
    • Journal of Microbiology and Biotechnology
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    • v.20 no.8
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    • pp.1210-1214
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    • 2010
  • Many bacteria are involved in the fermentation of doenjang, and Bacillus species are known to perform significant roles. Although SDS-PAGE has been frequently used to classify and identify bacteria in various samples, the microbial diversity in doenjang has not yet been investigated. This study aims to determine the identity and distribution of dominant Bacillus species in doenjang using SDS-PAGE profiles of whole-cell proteins and 16S rRNA gene sequencing. Reference Bacillus strains yielded differential SDS-PAGE banding patterns that could be considered to be highly specific fingerprints. Grouping of bacterial strains isolated from doenjang samples by whole-cell protein patterns was confirmed by analysis of their 16S rRNA gene sequences. B. subtilis was found to be the most dominant strain in most of the samples, whereas B. licheniformis and B. amyloliquefaciens were less frequently found but were also detected in several samples. The results obtained in this study show that a combined identification method using SDS-PAGE profiles of whole-cell proteins and subsequent 16S rRNA gene sequence analysis could successfully identify Bacillus species isolated from doenjang.