Abstract

A method for robustness optimization of flexible manufacturing systems is presented which undergoes forecasted product plan variations. A configuration of an FMS is modeled by a colored Petri net and the associated transition firing sequence. The robustness optimization of the colored Petri net model is formulated as an multi-objective optimization problem which minimizes production costs under multiple production plans, and reconfiguration cost due to production plan changes. As a first attempt, machines with limited flexibility are considered, and a genetic algorithm, coupled with a simple FIFO dispatching rule, is used to simultaneously find an semi-optimal resource allocation and event-driven schedule of a colored Petri net. The resulting Petri nets are then compared with the Petri nets optimized for a particular production plan in order to address the effectiveness of the robustness optimization for simultaneous production of products with different similarities. The simulation results suggest that the robustness optimization should be considered when the products are moderately different in their manufacturing processes.

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