TY - JOUR
T1 - A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems
AU - Hwang, Reakook
AU - Katayama, Hiroshi
PY - 2009/1
Y1 - 2009/1
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Assembly line balancing
KW - Assembly lines
KW - Evolutionary algorithms
KW - Genetic algorithms
KW - Global manufacturing
KW - Innovation management
KW - JIT performance measurement
KW - Kaizen
KW - Lean manufacturing
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U2 - 10.1080/00207540701851772
DO - 10.1080/00207540701851772
M3 - Article
AN - SCOPUS:70449632610
SN - 0020-7543
VL - 47
SP - 3797
EP - 3822
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 14
ER -