• Title/Summary/Keyword: machine-cell formation algorithm

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Machine Layout Decision Algorithm for Cell Formation Problem Using Self-Organizing Map (자기조직화 신경망을 이용한 셀 형성 문제의 기계 배치순서 결정 알고리듬)

  • Jeon, Yong-Deok
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.2
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    • pp.94-103
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    • 2019
  • Self Organizing Map (SOM) is a neural network that is effective in classifying patterns that form the feature map by extracting characteristics of the input data. In this study, we propose an algorithm to determine the cell formation and the machine layout within the cell for the cell formation problem with operation sequence using the SOM. In the proposed algorithm, the output layer of the SOM is a one-dimensional structure, and the SOM is applied to the parts and the machine in two steps. The initial cell is formed when the formed clusters is grouped largely by the utilization of the machine within the cell. At this stage, machine cell are formed. The next step is to create a flow matrix of the all machine that calculates the frequency of consecutive forward movement for the machine. The machine layout order in each machine cell is determined based on this flow matrix so that the machine operation sequence is most reflected. The final step is to optimize the overall machine and parts to increase machine layout efficiency. As a result, the final cell is formed and the machine layout within the cell is determined. The proposed algorithm was tested on well-known cell formation problems with operation sequence shown in previous papers. The proposed algorithm has better performance than the other algorithms.

A Machine Cell Formation Algorithm Using Network Partition (네트워크 분할 기법을 이용한 기계 그룹 형성 알고리즘)

  • Choi Seong-Hoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.27 no.3
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    • pp.106-112
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    • 2004
  • This paper presents a new heuristic algorithm for the machine cell(MC) formation problem. MC formation problem is represented as an unbalanced k-way network partition and the proposed algorithm uses four stage-approach to solve the problem. Four stages are natural sub-network formation, determination of intial vertexes for each sub-network, determination of initial partition, and improvement of initial partition. Results of experiments show that the suggested algorithm provides near optimal solutions within very short computational time.

A Cellular Formation Problem Algorithm Based on Frequency of Used Machine for Cellular Manufacturing System

  • Lee, Sang-Un
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.2
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    • pp.71-77
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    • 2016
  • There has been unknown polynomial time algorithm for cellular formation problem (CFP) that is one of the NP-hard problem. Therefore metaheuristic method has been applied this problem to obtain approximated solution. This paper shows the existence of polynomial-time heuristic algorithm in CFP. The proposed algorithm performs coarse-grained and fine-grained cell formation process. In coarse-grained cell formation process, the cell can be formed in accordance with machine frequently used that is the number of other products use same machine with special product. As a result, the machine can be assigned to most used cell. In fine-grained process, the product and machine are moved into other cell that has a improved grouping efficiency. For 35 experimental data, this heuristic algorithm performs better grouping efficiency for 12 data than best known of meta-heuristic methods.

A machine-cell formation method based on fuzzy set (퍼지 이론에 기초한 머신-셀 구성방법)

  • 이노성;임춘우
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1565-1568
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    • 1997
  • In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

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An integrated model of cell formation and cell layout for minimizing exceptional elements and intercell moving distance (예외적 요소와 셀간 이동거리를 최소화할 수 있는 셀 형성과 셀 배치결정 모형)

  • 윤창원;정병희
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.121-124
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    • 1996
  • In general, cellular manufacturing system can be constructed by the following two steps. The first step forms machine cells and part families, and the second step determines cell layout based on the result of first step. Cell layout has to be considered when cell is formed becauese the result of cell formation affects it. This paper presents a cell formation algorithm and proposes an integrated mathematical model for cell formation and cell layout. The cell formation algorithm minimizes the number of exceptional element in cellular manufacturing system. New concept for similarity and incapability is introduced, based on machine-operation incidence matrix and part-operation incidence matrix. One is similarity between the machines, the other is similarity between preliminary machine cells and machines. The incapability identifies relations between machine cells and parts. In this procedure, only parts without an exceptional element are assigned to machine cell. Bottleneck parts are considered with cell layout design in an integrated mathematical model. The integrated mathematical model determines cell layout and assigns bottleneck parts to minimize the number of exceptional element and intercell moving distance, based on linearixed 0-1 integer programming. The proposed algorithm is illustrated by using numerical examples.

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Cell Formation Algorithm for the Maximum Number of Cell without Exceptional Element in FMS with Alternative Routings (대체 가공경로를 갖는 FMS에서 예외적 요소가 존재하지 않는 최대수의 셀 형성방법)

  • Lee, Young-Kwang;Yun, Chang-Won;Chung, Byung-Hee
    • Journal of Korean Institute of Industrial Engineers
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    • v.20 no.2
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    • pp.51-64
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    • 1994
  • Cellular manufacturing requires formation of machine cells that can produce families of parts with similar processing requirement. The purpose of cell formation is to create separable machine clusters and part families simultaneously. However, the cell formation process often includes the identification of exceptional elements. This paper presents cell formation method under consideration of alternative routings in FMS which consists of machines capable of multi-processing and parts which require more than one operation. We suggest theorems to calculate the maximum number of machine cell and part family which have no exceptional elements. We also develop a cell formation algorithm which is based on the suggested theorem. A numerical example is provided to illustrate the proposed theorem and algorithm.

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A study on machine-cell formation in cellular manufacturing based on fuzzy set (퍼지집합에 기초한 셀 생산방식에서의 머신-셀 구성에 관한 연구)

  • Leam, Choon-Woo;Lee, Noh-Sung
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.305-310
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    • 1997
  • In this paper, a fuzzy set based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy logic is emoloyed to express the degree of appropriateness when alternative machines are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

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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 Study of Formation of Machine Cell-Part Family in FMS using the Simulated Annealing Algorithm (시뮬레이티드 어닐링 알고리즘을 이용한 유연생산시스템의 기계셀-부품군 형성에 관한 연구)

  • Kim, Jin-Yong;Park, Dae-Geuk;Oh, Byeong-Wan;Hong, Sung-Jo;Choi, Jin-Yeong
    • IE interfaces
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    • v.10 no.2
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    • pp.1-13
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    • 1997
  • The problem of the formation of machine-part cells in FMS is a very important issue at the planning and operating stages of FMS. This problem is inherently a combinatorial optimization problem, proven to be NP-complete(or, NP-hard). Among the several kinds of approaches which have been applied to solve the combinatorial optimization problems, the Simulated Annealing(SA) algorithm, a technique of random search type with a flexibility in generating alternatives, is a powerful problem solving tool. In this paper, the SA algorithm is used to solve machine cell-part family formation problems. The primary purpose of the study is to find the near-optimal solution of machine cell-part family formation problem, whare the product volume and number of operations are prespecified, that can minimize the total material handling cost caused by exceptional elements and intercell moves as much as possible. The results show that the SA algorithm is able to find a near-optimal solution for practical problems of the machine cell-part family formation.

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Design of Manufacturing Cell and Cellular Layout based on Genetic Algorithm (유전 알고리듬에 기초한 제조셀과 셀 배치의 설계)

  • Cho, Kyu-Kab;Lee, Byung-Uk
    • IE interfaces
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    • v.14 no.1
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    • pp.20-29
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    • 2001
  • This paper presents a concurrent design approach that deals with manufacturing cell formation and cellular layout in Cellular Manufacturing System. Manufacturing cell formation is to group machines into machine cells dedicated to manufacture of part families, and cellular layout problem determines layout of the manufacturing cells within shop and layout of the machines within a cell. In this paper, a concurrent approach for design of machine cell and cellular layout is developed considering manufacturing parameters such as alternative process plans, alternative machines, production volume and processing time of part, and cost per unit time of operation. A mathematical model which minimizes total cost consisting of machine installation cost, machine operating cost, and intercell and intracell movements cost of part is proposed. A hybrid method based on genetic algorithm is proposed to solve the manufacturing cell formation and cellular layout design problem concurrently. The performance of the hybrid method is examined on several problems.

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