Abstract
In apparel manufacturing, it is difficult to achieve line balance because the production rate of each workstation is different. This difficulty is particularly prominent in a labour-intensive assembly process. The development of a line balancing technique using genetic algorithms is thus proposed for optimizing the assignment of operatives in an assembly line. The impact of different levels of skill inventory SInon the assembly makespan is also investigated in order to find out the optimal number of task skills an operative should possess in the apparel assembly process. Experimental results will be discussed to demonstrate the performance of the proposed genetic optimization approach.
Original language | English |
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Title of host publication | Optimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI) |
Subtitle of host publication | From Production to Retail |
Publisher | Elsevier Inc. |
Pages | 153-169 |
Number of pages | 17 |
ISBN (Print) | 9780857097798 |
DOIs | |
Publication status | Published - 1 Jan 2013 |
Keywords
- Apparel manufacture
- Genetic algorithms
- Line balance
- Optimization
ASJC Scopus subject areas
- General Engineering