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dc.contributor.authorSu, CTen_US
dc.contributor.authorTong, LIen_US
dc.date.accessioned2019-04-02T05:59:15Z-
dc.date.available2019-04-02T05:59:15Z-
dc.date.issued1997-12-01en_US
dc.identifier.issn0166-3615en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0166-3615(97)00050-Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/149423-
dc.description.abstractIn integrated circuit (IC) fabrication, a wafer's defects tend to cluster. As the wafer size increases, the clustering phenomenon of the defects becomes increasingly apparent. When the conventional control chart (c chart) is used, the clustered defects frequently cause many false alarms. In this study, we propose a neural network-based procedure for the process monitoring of clustered defects in IC fabrication. The proposed procedure can reduce the phenomenon of the false alarms caused by the clustered defects. A case study is also presented to show the effectiveness of the proposed procedure. (C) 1997 Elsevier Science B.V.en_US
dc.language.isoen_USen_US
dc.subjectneural networksen_US
dc.subjectclustering analysisen_US
dc.subjectc charten_US
dc.subjectdefecten_US
dc.subjectclusteren_US
dc.titleA neural network-based procedure for the process monitoring of clustered defects in integrated circuit fabricationen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0166-3615(97)00050-Xen_US
dc.identifier.journalCOMPUTERS IN INDUSTRYen_US
dc.citation.volume34en_US
dc.citation.spage285en_US
dc.citation.epage294en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000071610600004en_US
dc.citation.woscount7en_US
Appears in Collections:Articles