• IE interfaces
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• v.10 no.3
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• pp.189-196
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• 1997

This paper presents a cell formation approach for a cellular manufacturing system to minimize the inter-cell moves considering operation sequences. Two new factors are introduced: (1)flow-similarity(FS) for integrating direct/indirect inter-machine flow and similarity (2)machine cell-part moves (CPM) for exactly computing inter-cell moves. FS is used for combining machines and CPM is used for assigning the parts to the preliminary machine cells. In addition, we develop an aggregated heuristic algorithm to form manufacturing machine cells and assign the parts to those cells based on these concepts. We use performance criterion called total inter-cell moves(TICM), which is the total material flow between internal cells and external cells. Results of computational tests on a number of randomly generated test problems show that the suggested heuristic is superior to existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.175-180
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• 2004

The machine-part group formation is to group the sets of parts having similar processing requirements into part families, and the sets of machines needed to process a particular part family into machine cells using grid computing. It forms machine cells from the machine-part incidence matrix by means of Self-Organizing Maps(SOM) whose output layer is one-dimension and the number of output nodes is the twice as many as the number of input nodes in order to spread out the machine vectors. It generates machine-part group which are assigned to machine cells by means of the number of bottleneck machine with processing part. The proposed algorithm was tested on well-known machine-part grouping problems. The results of this computational study demonstrate the superiority of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.143-151
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• 1996

The concept of cellular manufacturing is to decompose a manufacturing system into subsystems, which are easier to manage than the entire manufacturing system. The objective of cellular manufacturing is to group parts with similar processing requirements into part families and machines into cells which meet the processing needs of part families assigned to them. This paper presents a methodology for cell formation based on genetic algorithm which produces improved cell formation in terms of total moves, which is a weighted sum of both intercell moves and intracell moves. A sample problem is solved for two, three and four cells with an approach based on genetic algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.41-54
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• 2005

In this paper, we consider a multi-objective machine cell formation problem. This problem Is characterized as determining part route families and machine cells such that total sum of inter-ceil part movements and maximum machine workload imbalance are simultaneously minimized. Together with the objective function, alternative part routes and the machine sequences of part routes are considered In grouping Part route families. Due to the complexity of the problem, a two-phase heuristic algorithm is proposed. And we developed an n-stage look-ahead heuristic algorithm that generalizes the roll-out algorithm. Computational experiments were conducted to verify the performance of the algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.203-209
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• 1993

In Factory Automation environments such as FMS, the formation of machine-part based on GT should be considered. The purpose of this study is to develop a economic heuristic algorithm which considers various elements such as unit processing time, subcontract cost, and functional operation cost, machine processing capacity etc. When this proposed approach is applied to the real situation expected benefits are as follows: the reduction of production lead time work in process, labor force, tooling, rework and scrap, setup time, order time delivery, and paper work, etc.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.255-264
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• 1996

This Paper presents a heuristic algorithm for machine-part group formation considering part production information (Production volume, roution sequence, unit operation time, facility size) in cellular manufacturing logistics system. In general, factory space is restricted within limited size when cells are located. A twofold heuristic algorithm is developed for considering factory space restrictions of located cells. The first phase is a aggregation procedure to minimize inter cell movement for satisfactoring space restriction. The second phase is a rearrangement procedure to maximize line balancing efficiency between machines within the cell and non assigned machine during first phase. Numerical example is presented to verify the efficiency of proposed algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.263-266
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• 1998

Several constraints in machine duplication cost, machining capability, cell space capacity, intercell moves and exceptional elements(EEs) are main problems that prevent achieving the goal of ideal Cellular Manufacturin System (CMS) environment. Minimizing intercell part traffics and EEs are the main objective of the cell formation problem as it's a critical point that improving production efficiency. Because the intercell moves could be changed according to the sequence of operation, it should be considered in assigning parts and machines to machine cells. This paper presents a method that eliminates EEs under the constraints of machine duplication cost and cell space capacity attaining two goals of minimizing machine duplications and minimizing intercell moves simultaneously. Developing an algorithm that calculates the machine duplications by cell-machine incidence matrix and part-machine incidence matrix, and calculates the exact intercell moves considering the sequence of operation. Based on the number of machine duplications and exact intercell moves, the goal programming model which satisfying minimum machine duplications and minimum intercell moves is developed. A linear programming model is suggested that could calculates more effectively without damaging optimal solution. A numerical example is provided to illustrate these methods.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.87-96
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• 1998

Using the concept of cellular manufacturing systems(CMS) in job shop manufacturing system is one of the most innovative approaches to improving plant productivity. However. several constraints in machine duplication cost, machining capability, cell space capacity, intercell moves and exceptional elements(EEs) are main problems that prevent achieving the goal of maintaining an ideal CMS environment. Minimizing intercell part traffics and EEs are the main objective of the cell formation problem because it is a critical point that improving production efficiency. Because the intercell moves could be changed according to the sequence of operation, it should be considered in assigning parts and machines to machine ceil. This paper presents a method that eliminates EEs under the constraints of machine duplication cost and ceil space capacity attaining two goals of minimizing machine duplications and minimizing intercell moves simultaneously. Developing an algorithm that calculates the machine duplications by cell-machine incidence matrix and part-machine Incidence matrix, and calculates the exact intercell moves considering the sequence of operation. Based on the number of machine duplications and exact intercell moves, the goal programming model which satisfying minimum machine duplications and minimum intercell moves is developed. A linear programming model is suggested that could calculates more effectively without damaging optimal solution. A numerical example is provided to illustrate these methods.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.589-594
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• 1991

Group Technology (GT) is a technique for identifying and bringing together related or similar components in a production process in order to take advantage of their similarities by making use of, for example, the inherent economies of flow production methods. The process of identification, from large variety and total of components, of the part families requiring similar manufacturing operations and forming the associated groups of machines is referred as 'machine-component grouping'. First part of this paper is devoted to describing a hierarchical divisive algorithm based on graph theory to find the natural part families. The objective is to form components into part families such that the degree of inter-relations is high among components within the same part family and low between components of different part families. Second part of this paper focuses on establishing cell design procedures. The aim is to create cells in which the most expensive and important machines-called key machine - have a reasonably high utilization and the machines should be allocated to minimize the intercell movement of machine loads. To fulfil the above objectives, 0-1 integer programming model is developed and the solution procedures are found. Next an attempt is made to test the feasibility of the proposed method. Several different problems appearing in the literature are chosen and the results air briefly showed.