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dc.contributor.authorHuang, MGen_US
dc.contributor.authorChang, PLen_US
dc.contributor.authorChou, YCen_US
dc.date.accessioned2014-12-08T15:40:06Z-
dc.date.available2014-12-08T15:40:06Z-
dc.date.issued2003-11-20en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://dx.doi.org/10.1080/0020754031000149257en_US
dc.identifier.urihttp://hdl.handle.net/11536/27386-
dc.description.abstractTo achieve efficient and economical production, planners and/or designers of production systems frequently must evaluate manufacturing process similarities for various products that they intend to produce. Such work is particularly important in product-mix production, which is widely used in various production systems, including product-oriented repetitive manufacturing, cellular manufacturing, and process-oriented manufacturing. A new potential application for evaluating manufacturing process similarity is necessary in dealing with capacity exchange between rush orders and prescheduled orders. Traditionally, most evaluating methods assumed an essentially static environment, and merely compared the manufacturing routing, processing time and demand. Meanwhile, other more complex evaluating methods were simply impractical. This study suggests a relatively simple but practical method for evaluating the manufacturing process similarity within a dynamic bucketed production environment. The proposed algorithm considers load projection and workstation utilization in terms of a current production schedule. Finally, a real numerical instance is cited to illustrate the effectiveness of the proposed approach.en_US
dc.language.isoen_USen_US
dc.titleFast algorithm for evaluating the similarity of manufacturing processes within a dynamic production environmenten_US
dc.typeArticleen_US
dc.identifier.doi10.1080/0020754031000149257en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume41en_US
dc.citation.issue17en_US
dc.citation.spage4171en_US
dc.citation.epage4183en_US
dc.contributor.department經營管理研究所zh_TW
dc.contributor.departmentInstitute of Business and Managementen_US
dc.identifier.wosnumberWOS:000185909300011-
dc.citation.woscount6-
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