Congestion-aware dynamic routing for an overhead hoist transporter system using a graph convolutional gated recurrent unit

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Overhead hoist transportors (OHT) that transport semiconductor wafers between tools/stockers, is a crucial component of an Automated Material Handling System (AMHS). As semiconductor fabrication plants (FABs) become larger, more OHT vehicles need to be operated. This necessitates the development of a scalable algorithm to effectively operate these OHTs and increase the productivity of the AMHS. This study proposes an algorithm that can predict the entire traveling times of the edges in an OHT rail network by utilizing past traffic information. The model first represents the OHT rail network and the dynamic traffic conditions using a graph. A sequence of graphs that represent the past traffic is then used as an input to produce a sequence of graphs that predicts the future traffic conditions as an output. Using the AutoMod simulator, we have shown that the proposed model scalably and effectively predicts the future edge-traveling time. We have also demonstrated that the predicted values can be used to reroute the OHTs optimally to avoid congestion.
Publisher
TAYLOR & FRANCIS INC
Issue Date
2022-08
Language
English
Article Type
Article
Citation

IISE TRANSACTIONS, v.54, no.8, pp.803 - 816

ISSN
2472-5854
DOI
10.1080/24725854.2021.2000680
URI
http://hdl.handle.net/10203/296739
Appears in Collection
IE-Journal Papers(저널논문)
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