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Manufacturing Cell Design: An Integer Programming Model Employing Genetic Algorithms
 IIE Transactions
, 1996
"... The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest le ..."
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Cited by 15 (5 self)
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The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that intercell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.
Manufacturing Cell Formation by StateSpace Search
"... This paper addresses the problem of grouping machines in order to design cellular ..."
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Cited by 2 (1 self)
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This paper addresses the problem of grouping machines in order to design cellular
A Vector Perturbation Approach To The Generalized Aircraft Spare Parts Grouping Problem
, 2000
"... : The Vector Perturbation Approach is introduced for addressing the generalized parts grouping problem, identifying part families for a general set of suppliers, not just a single supplier. This method is driven by the need for flexible and lean supply chain systems. A vector space model is used to ..."
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Cited by 1 (1 self)
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: The Vector Perturbation Approach is introduced for addressing the generalized parts grouping problem, identifying part families for a general set of suppliers, not just a single supplier. This method is driven by the need for flexible and lean supply chain systems. A vector space model is used to represent a set of operation sequences as opposed to the traditional matrix and integer programming models in Group Technology. Using this approach we find that we are able to generate part groups from 90% of the available parts, in which all the operation sequences are preserved. This contrasts with only 66% of the available parts grouped using the traditional methods. Furthermore, a vector representation of operation sequences provides an intuitive means for discovering the natural structure of the part data. From these results we conclude that this technique can dramatically improve the effectiveness of the entire supply chain. INTRODUCTION A key challenge to military readiness is the a...
A Hybrid Genetic Algorithm for Manufacturing Cell Formation
"... Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach fo ..."
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Cellular manufacturing emerged as a production strategy capable of solving the problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining machine cells and product families. The approach combines a local search heuristic with a genetic algorithm. Computational experience with the algorithm on a set of group technology problems available in the literature is also presented. The approach produced solutions with a grouping efficacy that is at least as good as any results previously reported in literature and improved the grouping efficacy for 59 % of the problems. Keywords: Cellular Manufacturing; Group Technology; Genetic Algorithms; Random Keys AT&T Labs Research Technical Report TD5FE6RN, October 29, 2002.
Annals of Operations Research 65(1996)3554 35 Manufacturing cell formation by statespace search*
"... This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as ..."
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This paper addresses the problem of grouping machines in order to design cellular manufacturing ceils, with an objective to minimize intercell flow. This problem is related to one of the major aims of group technology (GT): to decompose the manufacturing system into manufacturing cells that are as independent as possible. This problem is NPhard. Thus, nonheuristic methods cannot address problems of typical industrial dimensions because they would require exorbitant amounts of computing time, while fast heuristic methods may suffer from poor solution quality. We present a branchandbound statespace search algorithm that attempts to overcome both these deficiencies. One of the major strengths of this algorithm is its efficient branching and search strategy. In addition, the algorithm employs the fast InterCell Traffic Minimization Method to provide good upper bounds, and computes lower bounds based on a relaxation of merging.
www.elsevier.com/locate/dsw An evolutionary algorithm for manufacturing cell formation *
, 2003
"... Cellular manufacturing emerged as a production strategy capable of solving the certain problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new app ..."
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Cellular manufacturing emerged as a production strategy capable of solving the certain problems of complexity and long manufacturing lead times in batch production. The fundamental problem in cellular manufacturing is the formation of product families and machine cells. This paper presents a new approach for obtaining machine cells and product families. The approach combines a local search heuristic with a genetic algorithm. Computational experience with the algorithm on a set of group technology problems available in the literature is also presented. The approach produced solutions with a grouping efficacy that is at least as good as any results previously reported in literature and improved the grouping efficacy for 59 % of the problems. q 2004 Published by Elsevier Ltd.
unknown title
, 2003
"... www.elsevier.com/locate/dsw Similarity coefficient methods applied to the cell formation problem: a comparative investigation ..."
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www.elsevier.com/locate/dsw Similarity coefficient methods applied to the cell formation problem: a comparative investigation
unknown title
"... Experiences of a small to medium size enterprise in the design and implementation of manufacturing cells ..."
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Experiences of a small to medium size enterprise in the design and implementation of manufacturing cells
Concurrent Cell Formation for Cellular Manufacturing System by Preemptive Fuzzy Goal Programming
"... Abstract—A new concurrent cell formation method for solving a Cell Formation (CF) problem in a Cellular Manufacturing System (CMS) is developed and proposed in this research. To solve such problem, conventionally a facility planner needs to classify parts into families and group machines into cells, ..."
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Abstract—A new concurrent cell formation method for solving a Cell Formation (CF) problem in a Cellular Manufacturing System (CMS) is developed and proposed in this research. To solve such problem, conventionally a facility planner needs to classify parts into families and group machines into cells, respectively. However, existing methods for solving the CF problem are difficult and complicated. Moreover, efficient solutions of some of those methods are not guarantee. So, the efficient method based on two important performance measures, called Exceptional Elements (EE) and the Void Elements (VE) of a perfect grouping, are developed. Preemptive Fuzzy Goal Programming (PFGP) is applied to these two performance measures for finding the efficient solution. The problems of grouping part family and machine cells can be simultaneously easily solved. Moreover, machines and parts grouping can also be adjustable to find preferred solutions by use of PFGP. The numerical examples existed in the literatures are shown to demonstrate the efficiency of the proposed model over the conventional method.