• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.23-32
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• 2009

• IE interfaces
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• v.9 no.2
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• pp.203-218
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• 1996

This paper deals with a Direct-Input-Output Manufacturing System (DIOMS) which has a number of machine centers placed along a built-in automated storage/retrieval system (AS/RS). During its operations, the storage/retrieval(S/R) machine picks up a pallet from the pickup/deposit port of a machine center and then moves it either to an empty rack opening of the AS/RS for temporary storage or to place it on the port of another machine center for subsequent operation. The machine layout problem in DIOMS is formulated as an integer mathematical programming whose objective is to minimize the total expected distance of the loaded S/R machine during a production period. Recognizing the limit of the exact solution procedure(the Branch and Bound method), two improvement-type heuristics are proposed. One is based on the simulated annealing method and the other the pairwise interchange method. The validity of the heuristics is examined with example problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.87-93
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• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.11-18
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• 2016

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

• 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.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.99-107
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• 2008

This paper is concerned with scheduling in Flexible Manufacturing Systems (FMS) using a Fuzzy Logic (FL) approach. Four fuzzy input variables: machine allocated processing time, machine priority, machine available time and transportation priority are defined. The job priority is the output fuzzy variable, showing the priority status of a job to be selected for the next operation on a machine. The model will first select the machines and then assign operations based on a multi-criteria scheduling scheme. System/machine utilization, minimizing mean flow time and balancing machine usage will be covered. Experimental and comparative tests indicate the superiority of this fuzzy based scheduling model over the existing approaches.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.45-55
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• 1986

A method for forming production cells in cellular manufacturing systems is presented. The basic approach is based on part-machine group formation by using relationship matrix calculated from the original part-machine matrix. The cases of exceptional elements and bottleneck machines are discussed. The proposed method can work with any starting form of part-machine matrix and provides the same solution regardless of the changes of starting form of part-machine matrix for any given problem.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.123-130
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• 1992

The group formation problem of the machine and part in Flexible Manufacturing System (FMS) is a very important issue in planning stage of FMS. This paper discusses the problem of machine-part group formation. The purpose of the study is to develop a heuristic algorithm, which can handle more realistic machine-part group formation problem by considering manufacturing factors. A new similarity coeffecient has been developed to solve more realistic machine-part group formation problem. For the purpose of illustations, a numerical example is presented.

• 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.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.113-125
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• 2008

This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.