首页 | 本学科首页   官方微博 | 高级检索  
     


A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems
Authors:ReaKook Hwang  Hiroshi Katayama
Affiliation:1. Department of Industrial and Management Systems Engineering , Waseda University , Tokyo, Japan rkhwang@kata.mgmt.waseda.ac.jp;3. Department of Industrial and Management Systems Engineering , Waseda University , Tokyo, Japan
Abstract:A mixed-model assembly line is a type of production line where a variety of product models similar in product characteristics are produced. As a consequence of introducing the just-in-time (JIT) production principle, it has been recognised that a U-shaped assembly line system offers several benefits over the traditional straight line system. This paper proposes a new evolutionary approach to deal with workload balancing problems in mixed-model U-shaped lines. The proposed method is based on the multi-decision of an amelioration structure to improve a variation of the workload. This paper considers both the traditional straight line system and the U-shaped assembly line, and is thus an unbiased examination of line efficiency. The performance criteria considered are the number of workstations (the line efficiency) and the variation of workload, simultaneously. The results of experiments enhanced the decision process during multi-model assembly line system production; thus, it is therefore suitable for the augmentation of line efficiency in workstation integration and simultaneously enhancement of the variation of the workload. A case study is examined as a validity check in collaboration with a manufacturing company.
Keywords:artificial intelligence  assembly line balancing  assembly lines  evolutionary algorithms  genetic algorithms  global manufacturing  lean manufacturing  innovation management  JIT performance measurement  kaizen
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号