This research explores analytical models useful in the design of vehicle-based Automated Material Handling Systems (AMHS) to support semiconductor manufacturing. The objective is to correctly estimate the throughput and move request delay. This analysis proposes a computationally effective analytical approach to multi-vehicle AMHS performance modeling for a simple closed loop. A probabilistic model is developed, based on a detailed description of AMHS operations, and the system is analyzed as an extended Markov chain. The model tracks the operations of one vehicle on the closed-loop considering the possibility of vehicle-blocking. This analysis provides the essential parameters such as the blocking probabilities in order to estimate the performance measures. A numerical example is analyzed and simulated using Automod to demonstrate and validate the queuing model.
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