Article ID: | iaor2004120 |
Country: | United Kingdom |
Volume: | 41 |
Issue: | 10 |
Start Page Number: | 2273 |
End Page Number: | 2299 |
Publication Date: | Jan 2003 |
Journal: | International Journal of Production Research |
Authors: | Abdi Mohammad Reza, Labib Ashraf W. |
Keywords: | decision theory: multiple criteria, analytic hierarchy process |
This paper presents Reconfigurable Manufacturing System (RMS) characteristics through comparison with conventional manufacturing systems in order to address a design strategy towards an RMS. The strategy is considered as a part of an RMS design loop to achieve a reconfigurable stategy over its implementation period. As another part of the design loop, a reconfiguration link between market and manufacturing is presented in order to group products into families (reconfiguring products) and then assign them to the required manufacturing processes over configuration stages. In particular, the Analytical Hierarchical Process (AHP) is employed for structuring the decision making process for the selection of a manufacturing system among feasible alternatives based on the RMS study. Manufacturing responsiveness is considered as the ability of using existing resources to reflect new environmental and technological changes quickly. The AHP model highlights manufacturing responsiveness as a new economic objective along with classical objectives such as low cost and high quality. The forward–backward process is then proposed to direct and control the design strategy under uncertain conditions during its implementation period. The proposed hierarchy is generic in structure and could be applicable to many firms by means of restructuring the criteria. The work is based on a case study in a manufacturing environment. Expert Choice software is applied to examine the structure of the proposed model and achieve synthesis/graphical results considering inconsistency ratios. The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Finally, to allocate available resources to the alternative solutions, a (0–1) knapsack formulation algorithm is represented.