Dynamic vehicle allocation in Automated Material Handling System

The Automated Materials Handling System (AMHS) in semiconductor industry is a significant to reduce the wafer cycle times and enhance the fab productivity. The determination of vehicle number, however, is challenging due to the complicated facility layout and the multiple reentries required in the manufacturing process. Previous research used to solve this problem based on the mathematical programming model, which does not take into account the highly variable and uncertain events in the process. In this research, we build a simulation model to account for the uncertainties existing in the manufacturing process. Furthermore, we propose a simulation optimization approach to solve the problem, i.e., to determine the optimal number of vehicles of the AMHS. An empirical study is conducted at the end to show the viability of the proposed method.