Multi-objective real-time dispatching for integrated delivery in a Fab using GA based simulation optimization

• We propose a simulation optimization methodology for the “integrated delivery” scheduling in a wafer fabrication Fab.
• A representative Pareto optimal solution subset is explored to take consideration of multiple objectives.
• The GA parameters optimization module and the proposed methodology are verified through a series of numerical experiments.
• An experimental bay of wafer fabrication Fab is used to illustrate the proposed approach can significantly improves the performance of the “integrated delivery system”

In a wafer fabrication Fab, the “integrated delivery”, which integrates the automated material handling system (AMHS) with processing tools to automate the material flow, is difficult to implement due to the system complexity and uncertainty. The previous dispatching studies in semiconductor manufacturing have mainly focused on the tool dispatching. Few studies have been done for analyzing combinatorial dispatching rules including lot dispatching, batch dispatching and automated guided vehicle (AGV) dispatching. To handle this problem, a GA (genetic algorithm) based simulation optimization methodology, which consists of the on-line scheduler and the off-line scheduler, is presented in this paper. The on-line scheduler is used to monitor and implement optimal combinatorial dispatching rules to the semiconductor wafer fabrication system. The off-line scheduler is employed to search for optimal combinatorial dispatching rules. In this study, the response surface methodology is adopted to optimize the GA parameters. Finally, an experimental bay of wafer fabrication Fab is constructed and numerical experiments show that the proposed approach can significantly improve the performance of the “integrated delivery system” compared with the traditional single dispatching rule approach.