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Automated Material Handling Systems (AMHS) are becoming more and more essential for economical working Megafabs. Managing large numbers of Work in Process (WIP) requires advanced logi!itical support strategies such that lots anive Just In Time at their destination, to minimize cycle time. This makes robust A M H S design mandatory with short delivery times, at least from the operators perspective. In order to compare system and layout altematives, appropriate metrics need to get defined, measured and compared. Traditionally, those altematives are evaluated with discrete event simulations. But it remains cumbersome to determine certain parameters like the overall availability. A new approach will be presented to address this issue. The methods described above have been applied to AMDs Fah 30, and the results are briefly discussed.

This survey sketches the importance of Automatic Control Engineering with all its flavors for state-of-the-art semiconductor manufacturing. Many automation disciplines are required for maximization of production yield, high throughput, low delivery times and little lateness. Tools for accomplishing these goals are hybrid dynamic modeling, advanced simulation and scheduling techniques, complex robustness calculations and comprehensive performance monitoring and justification methods.

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