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dc.contributor.authorWu, Muh-Cherngen_US
dc.contributor.authorChang, Wen-Jungen_US
dc.contributor.authorChiou, Chie-Wunen_US
dc.date.accessioned2014-12-08T15:16:20Z-
dc.date.available2014-12-08T15:16:20Z-
dc.date.issued2006-07-01en_US
dc.identifier.issn0268-3768en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s00170-005-2568-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/12112-
dc.description.abstractThe product mix decision problem for semiconductor manufacturing has been extensively studied in literature. However, most of them are based on a high-yield scenario. Yet, in a low-yield manufacturing environment, some research claims that scrap low-yield lots in an early stage may produce more profit. Considering the early scrapping characteristics, this paper aims to solve the product mix decision problem for a mixed-yield scenario, which involves the simultaneous production of high-yield and low-yield products. A nonlinear mathematical program is developed to model the decision problem. Two methods for solving the nonlinear program are proposed. Method 1 converts the nonlinear program into a linear program by setting some variables as parameters. The method provides an optimal solution by exhaustively searching these parameterized variables and solving the LP models iteratively. Method 2 aims to reduce the computation complexity while providing a near optimal solution. Experiment results show that method 2 is better than method 1, when aggregately considering solution quality and computation efforts.en_US
dc.language.isoen_USen_US
dc.subjectmixed-yield scenarioen_US
dc.subjectproduct mix planningen_US
dc.subjectscrappingen_US
dc.titleProduct-mix decision in a mixed-yield wafer fabrication scenarioen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00170-005-2568-2en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGYen_US
dc.citation.volume29en_US
dc.citation.issue7-8en_US
dc.citation.spage746en_US
dc.citation.epage752en_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:000238835600014-
dc.citation.woscount0-
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