• 한국기계가공학회지
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• 제13권6호
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• pp.30-36
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• 2014

Many different cells types have been found to be highly sensitive to mechanical force imposed by their surroundings. The cellular response to external mechanical forces has very important effects on numerous biological phenomena. In spite of its importance in biological processes, the cell adhesion force remains difficult to measure quantitatively at the cellular level. In this paper, to enhance quantitative measurements of cell adhesive interactions, a new attaching system and a method in which a glass bead can be attached to an AFM cantilever was designed and fabricated, and the degree of range displacement was controlled in the system. In an experiment, the movement of the stage in the attaching system and the attaching process were measured. The effectiveness of this system was confirmed as well in the experiment. In addition, through a commercial AFM system, the spring constant of the modified AFM probe could be measured.

• Industrial Engineering and Management Systems
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• 제7권2호
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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.

• 산업경영시스템학회지
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• 제22권50호
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• pp.45-54
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• 1999

Cellular manufacturing(CM) is a manufacturing philosophy and strategy for improving both productivity and flexibility. Cell formation(CF), the first and key problem faced in designing an effective CM system, is a process whereby parts with similar design features or processing requirements are grouped into part families, and the corresponding machines into machine cells. In this paper, a sophisticated fuzzy mixed-integer programming model is proposed to simultaneously form manufacturing cells and minimize the total costs of dealing with exceptional elements. Also, we will proposed a new method to solve the cell formation problem in the fuzzy environment.

• 산업경영시스템학회지
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• 제21권46호
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• pp.59-72
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• 1998

This study is concerned in manufacturing cell formation with operation sequences. Operation sequences must be reflected for manufacturing cell formation anyway, because the primary aim of cellular manufacturing system is to minimize the inter-cell flows, and inter-cell flows are differed by operation sequences. In this study we propose flow-similarity(FS) of reflecting both inter-machine similarity and direct/indirect flow, and then apply the modified P-median model for grouping machines. We also use machine cell-part handling frequency(CPH) so as to be assigned parts to the machine cells having the most CPH. We confirm this approach through an application example. The performance of this approach(FS-model) is evaluated and compared with P-median model and F-model through computational experiments.

• 산업경영시스템학회지
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• 제21권48호
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• pp.123-132
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• 1998

The group formation problem of the machine and part is a very important issue in the planning stage of cellular manufacturing systems. This paper investigates Self-Organizing Map(SOM) neural networks approach to machine-part grouping problem. We present a two-phase algorithm based on SOM for grouping parts and machines. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. Output layer in SOM network is one-dimensional structure and the number of output node has been increased sufficiently to spread out the input vectors in the order of similarity. The proposed algorithm performs remarkably well in comparison with many other algorithms for the well-known problems shown in previous papers.

• 경영과학
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• 제24권1호
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• pp.91-111
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• 2007

In this paper an effective two-phase approach adopting modified p-median mathematical model is proposed for grouping machines and parts in cellular manufacturing(CM). Unlike the conventional methods allowing machines and parts to be improperly assigned to cells and families, the proposed approach seeks to find the proper block diagonal solution where all the machines and parts are properly assigned to their most associated cells and families in term of the actual machine processing and part moves. Phase 1 uses the modified p-median formulation adopting new inter-machine similarity coefficient based on the non-binary production data-based part-machine incidence matrix(PMIM) that reflects both the operation sequences and production volumes for the parts to find machine cells. Phase 2 apollos iterative reassignment procedure to minimize inter-cell part moves and maximize within-cell machine utilization by reassigning improperly assigned machines and parts to their most associated cells and families. Computational experience with the data sets available on literature shows the proposed approach yields good-quality proper block diagonal solution.

• 한국컴퓨터정보학회논문지
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• 제21권2호
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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.

• 산업경영시스템학회지
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• 제23권61호
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• pp.23-31
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• 2000

This paper addresses the static operator allocation problem in celluar manufacturing systems(CMS). An assembly environment is considered where each component going into the final product is manufactured in an individual cell. There are m such cells and it is required to manufacture n varieties of products where n>m. An mathematical model and two heuristic algorithms for static operators allocation to the cells to balance workload for minimizing makespan are developed and tested.

• 한국경영과학회지
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• 제23권4호
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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.

• 한국산업정보학회논문지
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• 제16권4호
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• pp.119-125
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• 2011

The part family (PF) formation in a cellular manufacturing has been a key issue for the successful implementation of Group Technology (GT). Basically, a part has two different attributes; i.e., design and manufacturing. The respective similarity in both attributes is often conflicting each other. However, the two attributes should be taken into account appropriately in order for the PF to maximize the benefits of the GT implementation. This paper proposes a clustering algorithm which considers the two attributes simultaneously based on pareto optimal theory. The similarity in each attribute can be represented as two individual objective functions. Then, the resulting two objective functions are properly combined into a pareto fitness function which assigns a single fitness value to each solution based on the two objective functions. A GA is used to find the pareto optimal set of solutions based on the fitness function. A set of hypothetical parts are grouped using the proposed system. The results show that the proposed system is very promising in clustering with multiple objectives.