• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.72-80
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• 1998

In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.89-92
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• 1997

The objective of this paper is to provide an alternative framework for the integration of process planning and scheduling in cellular manufacturing. The concept of an integrated cellular manufacturing system is defined and the system architecture is presented. In an integrated cellular manufacturing system, there are three modules : the process planning module, the manufacturing-cell design module, and the cell-scheduling module. For each module, the tasks and their activities are explained.

• Journal of Power System Engineering
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• v.4 no.4
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• pp.92-98
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• 2000

Modern manufacturing systems should cope with the frequent changes in a product model and disturbances in manufacturing process. The control system of such systems must cover a constant adaptation and high flexibility. Holonic Flexible Manufacturing Cell(HFMC) is introduced to handle these issues more successfully. It is based on the concept of autonomous co-operating agent, called 'Holon', which is a building block of a manufacturing system for transforming, transporting, storing and/or validating information and physical objects. In this paper the basic structure of the HFMC is represented by using Unified Modeling Language and Open architecture cell controller is developed for effective integration components of a manufacturing system. Also a new control model, called MuLOM(Multi-Layered Operation Model), is suggested to represent the control behaviour for a holonic flexible manufacturing cell control system.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.25-33
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• 1992

Manufacturing cell formation is one of the most important problems faced in designing cellular manufacturing systems. The purpose of this study is to design effective manufacturing cell systems by developing a method which forms machines/parts into optimal machine cells/part families. The 0-1 data matrix structure is used to form a basis for manufacturing cell formation. In this paper, we propose a CE method to reorder the 0-1 data matrix for manufacturing cell formation. The resulting solutions are shown to demonstrate the effectiveness of the CE method.

• 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.

• Korean Management Science Review
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• v.12 no.1
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• pp.51-60
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• 1995

This paper presents a workload based model and cell design support system (CDSS) in manufacturing cell design. The proposed model consider manufacturing factor such as machine capacity, production volume, process time, and cell size. Based on those information, workload is calculated and according to the workload, the relationship between machine and part is represented by the workload matrix. To form the manufacturing cell, correlation similarity coefficient (CSC) among machines are calculated and a pair of machines that has the highest value of CSC is assigned to a machine cell. Repeat the above steps until the desired manufacturing cells are obtained. Finally, a cell design support system that could increase the efficiency in the application of a proposed model is developed. The proposed model and CDSS are illustrated by a numerical example.

• IE interfaces
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• v.17 no.spc
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• pp.152-159
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• 2004

The Purpose of this paper is to propose performance evaluation schemes of flexible manufacturing cell using a generalized stochastic Petri net. In the competitive and global manufacturing environment, to evaluate the feasibility and manufacturability of a product in the product design stage is highly required. Through this process, all the possible problems which may occur in the manufacturing stage can be fixed in early stage. The scheme of generalized stochastic Petri net utilizing both immediate and exponential distributed transitions are applied to model a manufacturing cell with flexible machines, material handler, transporter and buffers. Performance analyses are performed based on behavioral, structural and quantitative properties. A flexible manufacturing cell is evaluated using a Petri net simulator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.67-76
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• 1999

This research presents the relationship among machining time, cycle time and demand rate in a cellular manufacturing system. The manufacturing cell produces part families by automated machines. This paper discusses the cases of increasing demand rate in an existing cell and designing cell based on the demand rate. This research developed an algorithm for decision making such as cycle time, machines and workers in order to minimize the total machine capacity and the number of workers for any given demand rate. The proposed algorithm was successfully applied for the design and operation of cell manufacturing with a good result.

• 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.

• 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.