• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.121-128
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• 2005

This paper proposes the heuristic approach for the generalized GT(Group Technology) problem to consider the restrictions which are given the number of cell, maximum number of machines and minimum number of machines. This approach is classified into two stages. In the first stage, we use the similarity coefficient method which is proposed and calculate the similarity values about each pair of all machines and align these values in descending order. If two machines which is selected is possible to link the each other on the edge of machine cell and they don't have zero similarity value, then we assign the machines to the machine cell. In the second stage, it is the course to form part families using proposed grouping efficacy. Finally, machine-part incidence matrix is realigned to block diagonal structure. The results of using the proposed approach are compared to the Modified p-median model.

• 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.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.187-197
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• 2004

The recycling cell formation problem means that disposal products are classified into recycling product families using group technology in their end-of-life phase. Disposal products have the uncertainties of product condition usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a new approach for the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy ART neural networks are applied to describe the condition of disposal product with the membership functions and to make recycling cell formation. The approach leads to cluster materials, components, and subassemblies for reuse or recycling and can evaluate the value at each cell of disposal products. Disposal refrigerators are shown as an example.

• 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.

• 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.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.115-125
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• 2005

This paper discusses how to effectively design a next-generation wireless communication system that can possibly provide very high data-rate transmissions and versatile quality services. In order to accommodate the sophisticated user requirements and diversified user environments of the next-generation systems, it should be designed to take an efficient and flexible structure for multiple access and resource allocation. In addition, the design should be optimized for cost-effective usage of resources and for efficient operation in a multi-cell environment. As orthogonal frequency division multiple access (OFDMA) has turned out in recent researches to be one of the most promising multiple access techniques that can possibly meet all those requirements through efficient radio spectrum utilization, we take OFDMA as the basic framework in the next-generation wireless communications system design. So, in this paper, we focus on introducing an OFDMA-based downlink system design that employs the techniques of hybrid multiple access (HMA) and frequency group (FG) in conjunction with intra-frequency group averaging (IFGA). The HMA technique combines various multiple access schemes on the basis of OFDMA system, adopting the multiple access scheme that best fits to the given user condition in terms of mobility, service, and environment. The FG concept and IFGA technique help to reduce the feedback overhead of OFDMA system and the other-cell interference (OCI) problem by grouping the sub-carriers based on coherence band-widths and by harmonizing the channel condition and OCI of the grouped sub-carriers.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.83-92
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• 2012

This paper suggests an improved method of grouping minterms based on the Decimal-Valued Matrix (DVM) method. The DVM is a novel approach to Boolean logic minimization method which was recently developed by this author. Using the minterm-based matrix layout, the method captures binary number based minterm differences in decimal number form. As a result, combinable minterms can be visually identified. Furthermore, they can be systematically processed in finding a minimized Boolean expression. Although this new matrix based approach is visual-based, the suggested method in symmetric grouping cell values can become rather messy in some cases. To alleviate this problem, the enhanced DVM method that is based on multi-level groupings of combinable minterms is presented in this paper. Overall, since the method described here provides a concise visualization of minterm groupings, it facilitates a user with more options to explore different combinable minterm groups for a given Boolean logic minimization problem.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.5
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• pp.9-19
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• 2011

In many instances a concise form of logic is often required for building today's complex systems. The method described in this paper can be used for a wide range of industrial applications that requires Boolean type of logic minimization. Unlike some of the previous logic minimization methods, the proposed method can be used to better gain insights into the logic minimization process. Based on the decimal valued matrix, the method described here can be used to find an exact minimized solution for a given Boolean function. It is a visual based method that primarily relies on grouping the cell values within the matrix. At the same time, the method is systematic to the extent that it can also be computerized. Constructing the matrix to visualize a logic minimization problem should be relatively easy for the most part, particularly if the computer-generated graphs are accompanied.