Increasing global competition, rapid changes in technology and the necessity to respond quickly to a cost and quality conscious customer have changed the dynamics of facilities planning. Today's manufacturing facility needs to be responsive to the frequent changes in product mix and demand while minimizing material handling and machine relocation costs. In this paper, we present a framework for the design of a dynamic facility which can respond e ectively to the changes in product design, mix and volume in a continuously evolving work environment. A genetic algorithm-based heuristic is used for solving the design problem and two test cases are presented to illustrate the use of the methodology.
IntroductionIn a typical manufacturing plant, a manufacturing engineer decides on the sequence of operations that are necessary to transform the raw materials into ® nished products. This set of operations, along with previously established cost and quality criteria help determine suitable manufacturing equipment. Based on this selection and knowledge of the interaction between various machining centres or departments, the facility designer attempts either to maximize an adjacency measure, minimize the total cost of material handling or optimize some combination of the two. A heuristic or an optimal algorithm (depending on the formulation and size of the problem) is used to obtain a block layout. The solution is then modi® ed to include qualitative or non-quanti® able criteria. Such models often assume that:
The objective of most facility layout problems is to minimize material handling cost, which is directly proportional to both the distance between the machines and the mix, as well as the volume of products handled. The mix and volume of products are dependent on the demand patterns, and the distance is dependent on the layout plan used for the facility. Because it is relatively di cult to change the demand patterns, and hence the mix and volume of products, the primary focus of most designers has been to deal with the distance attribute of the material handling costs.The limitations of available horizontal space create a need to explore vertical expansion of facilities. This brings up new aspects of vertical material handling and¯ow that need to be considered in the facility design problem. In this paper, we present a genetic algorithm-based heuristic for generating block layouts for multiple-¯oor layout problems. This approach produces better solutions than existing simulated annealing-based heuristics for all but one of ® ve multipleoor test problems available in the literature.
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