A comparative evaluation of some group-technology scheduling heuristics.
Item
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Title
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A comparative evaluation of some group-technology scheduling heuristics.
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Identifier
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AAI9020786
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identifier
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9020786
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Creator
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Metwally, Amal Fathy.
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Contributor
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Adviser: David G. Dannenbring
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Date
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1990
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Language
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English
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Publisher
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City University of New York.
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Subject
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Business Administration, General | Engineering, Industrial
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Abstract
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Group technology is an innovative approach to increase efficiency and productivity of small-, and medium-batch production by grouping similar parts together in families, and arranging the machines required to process these families into cells.;By doing this, GT can achieve economic advantages similar to those associated with continuous flow-line production. GT implementation can reduce setup times, simplify materials flow, increase capacity, and improve production planning and control. But the great potential of GT is the role it can play in integrating modern manufacturing- and information-related technologies and systems, such as integrating Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) in Computer-Integrated Manufacturing (CIM). GT also provides the cellular manufacturing concept which is applied in Flexible Manufacturing Systems.;Because of this important role that GT can play, and for its expected advantages, this study concentrates on one of the major areas of GT application, which is production scheduling. The scheduling problem is greatly simplified, and its scope is also reduced by using GT.;The study investigates and compares the performance of five different scheduling heuristics in a GT flow line to minimize the maximum flow time (makespan). Three of these heuristics were originally developed for use in the conventional flow shop, and they have been adjusted in this study for use in a static, deterministic group-technology flow line. The other two heuristics are new versions of a conventional flow shop scheduling heuristic.;Besides evaluating performance of these five heuristics, the effects of some operational factors are also tested, including the impact of problem size in general, and in particular, the impact of the number of families, the number of jobs within each family, and the number of machines on performance of the heuristics. The impact of the range of group setup time on the relative performance of heuristics is also tested.;Computational results for a variety of small and large problems are presented. Conclusions and directions for future work are also reported.
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Type
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dissertation
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Source
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PQT Legacy CUNY.xlsx
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degree
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Ph.D.
