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ROBUSTNESS OPTIMIZATION OF FMS UNDER PRODUCTION PLAN VARIATIONS: THE CASE OF CYCLIC PRODUCTION

This paper discusses an extension of our previous work (Saitou, 1998) on robustness optimization of flexible manufacturing systems (FMS) that undergo forecasted production plan variations. The extension is made to a more general class of FMS performing “non-linear” or “cyclic” production that allows multiple operation types per one machine type. As in our previous work (Saitou, 1998), a configuration of an FMS is modeled as a colored Petri net and the associated transition firing sequence, and the robustness of FMS is defined as the insensitivity of production performances against variations in production plan. The optimization of the robustness of the colored Petri net model is formulated as a multi-objective optimization problem which minimizes production costs under multiple production plans (batch sizes for all jobs), and reconfiguration cost due to production plan changes. A genetic algorithm, coupled with a dispatching rule based on shortest imminent operation time (SIO), 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. The simulation results suggest that the proposed robustness optimization scheme should be considered when the products are moderately different in their job specifications so that optimizing for a particular production plan creates inevitably bottlenecks in product flow and/or deadlock under other production plans.