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dc.contributor.authorWang, Yi-Chien_US
dc.contributor.authorChen, Tin-Chih Tolyen_US
dc.date.accessioned2019-08-02T02:24:21Z-
dc.date.available2019-08-02T02:24:21Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn2351-9789en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.promfg.2018.10.021en_US
dc.identifier.urihttp://hdl.handle.net/11536/152485-
dc.description.abstractYield forecasting is a critical task to every semiconductor manufacturer. However, the existing methods for yield forecasting often deal with the logarithmic or log-sigmoid value, rather than the original value, of yield. To resolve this problem, in this study, the fuzzy collaborative intelligence (FCT) method proposed by Chen and Tin (2008) is modified, so that it can consider the original value of yield directly. The modified FCI method is called the direct-solution (DS)-FCI approach. The effectiveness oldie DS-FCI approach was validated with a real case. The experimental results showed that the DS-FCT approach outperformed Chen and Tin's FCI method in improving the forecasting accuracy and precision. (C) 2018 The Authors. Published by Elsevier B.V.en_US
dc.language.isoen_USen_US
dc.subjectyielden_US
dc.subjectforecastingen_US
dc.subjectdirect-solveen_US
dc.subjectsemiconductoren_US
dc.titleA Direct-solution Fuzzy Collaborative Intelligence Approach for Yield Forecasting in Semiconductor Manufacturingen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1016/j.promfg.2018.10.021en_US
dc.identifier.journal28TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING (FAIM2018): GLOBAL INTEGRATION OF INTELLIGENT MANUFACTURING AND SMART INDUSTRY FOR GOOD OF HUMANITYen_US
dc.citation.volume17en_US
dc.citation.spage110en_US
dc.citation.epage117en_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:000471035200014en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper