A performance model of automated material handling systems with double closed-loops and shortcuts in 300 mm semiconductor wafer fabrication systems

Abstract

Automated material handling systems (AMHSs) with double closed-loops and shortcuts have been widely adopted by general 300mm semiconductor fabrication enterprises due to their higher transportation efficiency, more flexible vehicle routing, and lower vehicle congestion compared with those traditional ones with single-loop. An accurate and efficient performance analysis model is crucial to quickly and effectively evaluate the schemes in the early stage of AMHS design. This paper proposes an extended Markov chain model (EMCM) to rapidly and effectively analyze performances of the AMHS with double closed-loops and shortcuts. In the modeling process, the inner closed-loop and shortcuts are abstracted as virtual stations to discretely express the running process of overhead hoist transporters (OHTs) on them. OHT’s running process in AMHS is discretized and equivalent to the state change of Markov chain and a triple-structure model is presented to describe the Markov states, so that the system characteristics, including OHT blockage, system’s double closed-loops, and shortcuts configuration, can be fully considered. The complex Markov process with multiple OHTs is transformed into the process with multiple independent OHTs so as to effectively eliminate the model’s state space explosion. System state probabilities models and blocking probability models are built to effectively represent its state and blocking properties. The stability state equations of EMCM are built so that its steady-state visit ratio can be identified. With production data from a semiconductor fabrication enterprise, the proposed performance analysis model is compared with a simulation model. The result shows that two models have a small relative error in the aspect of empty OHT’s mean arrival time interval, interbay throughput capacity, and OHT’s mean utilization ratio. However, the computing efficiency of the EMCM is significantly higher than that of the simulation model. It demonstrates that the proposed EMCM is effective and efficient for performance analysis in the early stage of AMHS design.