In the semiconductor and display industries, the automated material handling system (AMHS) represents an important component of fabrication facilities, which typically cost more than multi-billions of US dollars to build. One unit of fabrication facility consists of hundreds of processing steps with hundreds of expensive toolsets, and a production unit is completed after traveling over 9[Formula: see text]km for more than a month in the facility. Since all material handlings within the fabrication facility are performed by AMHS with minimal human intervention, the proper capacity of AMHS plays a very important role in fabrication operation. If the capacity is too large, it wastes the capacity of the production process as it potentially occupies too much space and investment. On the other hand, if the capacity of AMHS is too small, products under processing cannot be delivered to the expensive process toolsets on time, which causes a drop in productivity. This paper proposes an analytical method for assessing capacity planning strategies for the AMHS under various ramp-up scenarios. It proposes an analytical model consisting of three cost elements including fixed, operating, and delay costs measured by Erlang’s loss system to evaluate various investment alternatives based on the cost-of-ownership approach. We carefully prepared input data based on expert opinions to conduct an experiment that considers investment estimates for the three hypothetical alternatives. The experimental results illustrate that one-step strategy or lead strategy should be used depending on the fabrication facility’s ramp-up speed, which can be analyzed by the model proposed by this paper.