Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145527
Title: Scheduling dual-arm cluster tools with multiple wafer types and residency time constraints
Authors: Wang, Jipeng
Hu, Hesuan
Pan, Chunrong
Zhou, Yuan
Li, Liang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Wang, J., Hu, H., Pan, C., Zhou, Y., & Li, L. (2020). Scheduling dual-arm cluster tools with multiple wafer types and residency time constraints. IEEE/CAA Journal of Automatica Sinica, 7(3), 776-789. doi:10.1109/JAS.2020.1003150
Journal: IEEE/CAA Journal of Automatica Sinica 
Abstract: Accompanying the unceasing progress of integrated circuit manufacturing technology, the mainstream production mode of current semiconductor wafer fabrication is featured with multi-variety, small batch, and individual customization, which poses a huge challenge to the scheduling of cluster tools with single-wafer-type fabrication. Concurrent processing multiple wafer types in cluster tools, as a novel production pattern, has drawn increasing attention from industry to academia, whereas the corresponding research remains insufficient. This paper investigates the scheduling problems of dual-arm cluster tools with multiple wafer types and residency time constraints. To pursue an easy-to-implement cyclic operation under diverse flow patterns, we develop a novel robot activity strategy called multiplex swap sequence. In the light of the virtual module technology, the workloads that stem from bottleneck process steps and asymmetrical process configuration are balanced satisfactorily. Moreover, several sufficient and necessary conditions with closed-form expressions are obtained for checking the system's schedulability. Finally, efficient algorithms with polynomial complexity are developed to find the periodic scheduling, and its practicability and availability are demonstrated by the offered illustrative examples.
URI: https://hdl.handle.net/10356/145527
ISSN: 2329-9266
DOI: 10.1109/JAS.2020.1003150
Schools: School of Computer Science and Engineering 
Rights: © 2020 the Chinese Association of Automation. All rights reserved. This paper was published in IEEE/CAA Journal of Automatica Sinica and is made available with permission of the Chinese Association of Automation.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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