Scheduling Dual-Armed Cluster Tools with Chamber Cleaning Operations

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dc.contributor.authorYu, Tae Sunko
dc.contributor.authorLee, Tae-Eogko
dc.date.accessioned2019-02-20T04:46:15Z-
dc.date.available2019-02-20T04:46:15Z-
dc.date.created2018-06-12-
dc.date.issued2019-01-
dc.identifier.citationIEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, v.16, no.1, pp.218 - 228-
dc.identifier.issn1545-5955-
dc.identifier.urihttp://hdl.handle.net/10203/250175-
dc.description.abstractCircuit widths and nodes of semiconductor wafers have been continually shrinking down to less than 20 nm. Therefore, modern wafer fabs enforce extremely strict process control to prevent wafer quality failures. A wafer processing chamber is now frequently cleaned to remove residual chemicals and impurities. Yu et al. show that such cleaning operations significantly change the tool operation of single-armed cluster tools, and they suggest an idea of partial wafer loading to improve the tool throughput under cleaning requirements. However, little is known about how a dual-armed tool could be effectively scheduled when chamber cleaning exists. A dual-armed robot allows more flexible tool operational sequences, and hence, the scheduling problem becomes further complicated and challenging. In this paper, we propose a scheduling method by which the dual arms can be properly exploited for better tool productivity. We show that the suggested hybrid sequence significantly reduces the tool cycle time as compared to previously developed scheduling methods. Through this research, we conclude that the productivity gain of the dual arms against single arm is more significant when chambers are cleaned.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleScheduling Dual-Armed Cluster Tools with Chamber Cleaning Operations-
dc.typeArticle-
dc.identifier.wosid000455723500018-
dc.identifier.scopusid2-s2.0-85034272237-
dc.type.rimsART-
dc.citation.volume16-
dc.citation.issue1-
dc.citation.beginningpage218-
dc.citation.endingpage228-
dc.citation.publicationnameIEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING-
dc.identifier.doi10.1109/TASE.2017.2764105-
dc.contributor.localauthorLee, Tae-Eog-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
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