Article ID: | iaor2007108 |
Country: | United Kingdom |
Volume: | 44 |
Issue: | 11 |
Start Page Number: | 2091 |
End Page Number: | 2117 |
Publication Date: | Jan 2006 |
Journal: | International Journal of Production Research |
Authors: | Liang M., Xu Z. |
Keywords: | heuristics: genetic algorithms |
To take full advantage of product modularity, modular product design and assembly system design/reconfiguration have to be simultaneously addressed. The emerging reconfigurable production and flexible assembly techniques have made such an integrated approach possible. As such, this paper proposes an integrated approach to product module selection and assembly line design/reconfiguration problems. It further suggests that quality loss functions be used in a generic sense to quantify non-comparable and possibly conflicting performance criteria involved in the integrated problem. The complexity of the problem precludes the use of commercial software for solving meaningful sized problems in polynomial time. A genetic algorithm is therefore developed to provide quick solutions. An example problem is solved to illustrate the application of the proposed approach. Based on 72 randomly generated test problems, ANOVA analysis is further carried out to investigate the effects of genetic algorithm parameters. The convergence behaviour of the search processes is also examined by solving large problems with different numbers of operations and product modules.