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dc.contributor.authorWu, MCen_US
dc.contributor.authorChiou, CWen_US
dc.contributor.authorHsu, HMen_US
dc.date.accessioned2014-12-08T15:39:42Z-
dc.date.available2014-12-08T15:39:42Z-
dc.date.issued2004-02-01en_US
dc.identifier.issn0894-6507en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TSM.2003.822732en_US
dc.identifier.urihttp://hdl.handle.net/11536/27108-
dc.description.abstractSome wafers in a lot may become spoiled after they are processed at a workstation; such a lot is called a small lot. In a low yield and high price scenario, scrapping small lots may increase revenue and profit; yet, this notion has seldom been examined. This study presents a model for formulating the decision-making problem of scrapping small lots. A genetic algorithm is used to solve the problem when the solution space is large. An exhaustive search method is used when the solution space is small. Some numerical examples are used to evaluate the outcome of scrapping small lots. The profit obtained by the proposed scrapping method may be up to 23% higher than that obtained without scrapping.en_US
dc.language.isoen_USen_US
dc.subjectbottlenecken_US
dc.subjecthigh priceen_US
dc.subjectlow yielden_US
dc.subjectproduct introductionen_US
dc.subjectsmall lotsen_US
dc.titleScrapping small lots in a low-yield and high-price scenarioen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TSM.2003.822732en_US
dc.identifier.journalIEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURINGen_US
dc.citation.volume17en_US
dc.citation.issue1en_US
dc.citation.spage55en_US
dc.citation.epage67en_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:000188807600007-
dc.citation.woscount2-
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