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Effects Of Spreading-Table Quantities On The Spreading-Table Planning Of Computerized Fabric-Cutting System

Effects Of Spreading-Table Quantities On The Spreading-Table Planning Of Computerized... Many researches have been conducted on the production planning problems. Recently, genetic algorithms have been applied to solve this problem. No studies have been discussed to solve the production planning problem in the operations of fabric spreading and cutting in garment manufacturing. A non-optimized spreading-table planning will directly causes poor work balance with idle time on the computerized fabric-cutting system. As a result, delay for delivery of cut pieces to the sewing operations happens. One of the factors greatly influencing the final spreading and cutting planning is the quantities of spreading tables installed. This paper presents a genetic algorithm (GA) approach to investigate an optimized spreading-table planning for the computerized fabric-cutting system and the effects of different quantities of spreading table on the spreading-table planning. The results show that GA is an effective approach to find out the optimized planning for the cutting system and predict the effects of different number of spreading tables on the production planning. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Research Journal of Textile and Apparel Emerald Publishing

Effects Of Spreading-Table Quantities On The Spreading-Table Planning Of Computerized Fabric-Cutting System

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References (9)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1560-6074
DOI
10.1108/RJTA-04-01-2000-B003
Publisher site
See Article on Publisher Site

Abstract

Many researches have been conducted on the production planning problems. Recently, genetic algorithms have been applied to solve this problem. No studies have been discussed to solve the production planning problem in the operations of fabric spreading and cutting in garment manufacturing. A non-optimized spreading-table planning will directly causes poor work balance with idle time on the computerized fabric-cutting system. As a result, delay for delivery of cut pieces to the sewing operations happens. One of the factors greatly influencing the final spreading and cutting planning is the quantities of spreading tables installed. This paper presents a genetic algorithm (GA) approach to investigate an optimized spreading-table planning for the computerized fabric-cutting system and the effects of different quantities of spreading table on the spreading-table planning. The results show that GA is an effective approach to find out the optimized planning for the cutting system and predict the effects of different number of spreading tables on the production planning.

Journal

Research Journal of Textile and ApparelEmerald Publishing

Published: Feb 1, 2000

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