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dc.contributor.author巫木誠en_US
dc.contributor.authorWU MUH-CHERNGen_US
dc.date.accessioned2014-12-13T10:42:37Z-
dc.date.available2014-12-13T10:42:37Z-
dc.date.issued2011en_US
dc.identifier.govdocNSC99-2221-E009-110-MY3zh_TW
dc.identifier.urihttp://hdl.handle.net/11536/99274-
dc.identifier.urihttps://www.grb.gov.tw/search/planDetail?id=2206871&docId=352205en_US
dc.description.abstract步進機是晶圓廠產出的瓶頸,其生產排程的研究一直很受重視。過去文獻都採「巨 觀塑模」分析,將一部步進機當成單機來排程,這種研究方法,只能應用於「高良率」 情境;若應用於「低良率」情境,會因塑模過於粗略,造成步進機產能損失而不知。有 鑑於此,本研究提出一個三年期的專題計畫,來探討步進機在「新製程導入」情境下的 排程研究。本研究擬改採用「微觀塑模」分析,亦即,將一部步進機更細部解構,看成 是一個特殊的流線型工廠,並藉此微觀模型,發展各種排程方法來提升步進機的產出率。 本計畫各年度的研究範疇規劃如下。第一年主要是研究單機排程,決策變數只有一 個維度,就是工件的排序。第二年研究範疇為多機排程,決策變數增擴為兩個維度,包 括:工件指派、工件排序。第三年研究範疇為家族式派工的多機排程,決策變數增擴為 三個維度,包括:工件指派、家族間工件排序、家族內工件排序。 各年度所擬採用之研究方法,基本上有下列四種:隨機式進化搜尋法,數學規劃法; 發展新的染色體解讀法,發展多染色體表達法。各年度將根據實證結果,逐步改良所發 展的演算法。本研究議題不僅有學術創意,也有工業實用性,研究成果應可幫助提升我 國晶圓廠的國際競爭力。zh_TW
dc.description.abstractIn-line steppers (simply called steppers) are the bottleneck of a semiconductor wafer fab, and their scheduling has been extensively investigated. Prior literature adopts a macro-level modeling paradigm, in which a stepper is taken as a single machine. Using such a paradigm is appropriate in a high-yield scenario, but may not be so in a low-yield scenario. In practice, low-yield scenarios are not uncommon due to frequent introduction of new processes. We thus propose a 3-year project to investigate the scheduling of in-line steppers in new process introduction (NPI) scenarios. In the project, we attempt to use a micro-level modeling paradigm, in which an in-line stepper is taken as a featured flow shop, and develop various scheduling algorithms in order to increase the productivity of in-line steppers. The research scope of each year is described below. In the 1st year, we focus on single machine scheduling, which includes only one-dimensional decision variables (job sequencing). In the 2nd year, we extend the scope to the scheduling of multiple machines—which include two-dimensional variables (job allocation and job sequencing). In the 3rd year, we further extend the scope to family-based scheduling of multiple machines—which include three-dimensional variables (job allocation, among-family sequencing, and within-family sequence). Four solution approaches will be examined: evolutionary search algorithms, mathematical programming, chromosome representation schemes, and chromosome interpretation schemes. This research project is not only unique in academic merit and has a significant effect in increasing the productivity of in-line steppers, which in turn substantially influence the ultimate performance of a wafer fab.en_US
dc.description.sponsorship行政院國家科學委員會zh_TW
dc.language.isozh_TWen_US
dc.subject排程zh_TW
dc.subject半導體zh_TW
dc.subject流線型工廠zh_TW
dc.subject裝載產能限制zh_TW
dc.subject基因演算法zh_TW
dc.subjectschedulingen_US
dc.subjectsemiconductoren_US
dc.subjectflowshopen_US
dc.subjectport capacity constraintsen_US
dc.subjectgenetic algorithmen_US
dc.title新製程導入情境下連線式步進機之排程zh_TW
dc.titleScheduling of In-Line Steppers in New Process Introduction Scenariosen_US
dc.typePlanen_US
dc.contributor.department國立交通大學工業工程與管理學系(所)zh_TW
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