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dc.contributor.author涂凱文en_US
dc.contributor.authorKai-Wen Tuen_US
dc.contributor.author盧鴻興en_US
dc.contributor.authorHorng-Shing Luen_US
dc.date.accessioned2014-12-12T02:57:49Z-
dc.date.available2014-12-12T02:57:49Z-
dc.date.issued2007en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT009326802en_US
dc.identifier.urihttp://hdl.handle.net/11536/79304-
dc.description.abstract在半導體產業, 機台表現之比較是提升量率的關鍵之一, 我們發展一套新的統計方法, TCP.不但可以適用在機台使用率不相同造成之樣本數不同之現象亦可主動依工程師設定之工程忍受度將機台分群,可大幅縮短工程師分析機台表現之時間,我們將提供統計模擬來說明我們方法之優點也提供兩個半導體業界之實例說明我們的方法可適用在量率提升與製程能力提升zh_TW
dc.description.abstractIn the semiconductor industry, tool comparison is a key task in the yield and the product quality enhancements. We developed a new method, called tolerance control partitioning (TCP), to automatically partition tools into several homogenous groups based on the related metrology results. This methodology is based on a hierarchical normal model and the implementation is carried out using a Bayesian approach. There are several advantages of using the TCP method. First, it takes into account the unbalanced usage of the tools in the manufacturing processes. Moreover, the “engineer’s tolerance control” can be incorporated into the TCP method via the specification of the priors in the Bayesian analysis, which justifies the significant difference between groups according to the experts’ knowledge. This specification not only has the advantage of adjusting the number of partition groups but also avoids the problem of having too many partition groups with small differences which is often encountered in the conventional approaches. Some simulation results illustrate the advantages of the TCP method compared to the method of classification and regression trees (CART). Moreover, the TCP method is applied to two real examples for the yield and Cp/Cpk enhancement in the semiconductor industry. Both results confirm the practical usefulness of the proposed method. For general applications, the TCP method is also useful for other similar problems such as the comparisons between several experimental recipes or the comparisons between different materials.en_US
dc.language.isoen_USen_US
dc.subject貝氏分析zh_TW
dc.subject資料探勘zh_TW
dc.subjectRJMCMCzh_TW
dc.subjectCARTzh_TW
dc.subject量率提升zh_TW
dc.subject製程能力指標zh_TW
dc.subjectAPCzh_TW
dc.subjectBayesian fiten_US
dc.subjectdata miningen_US
dc.subjectreversible jump Markov chain Monte Carloen_US
dc.subjectCARTen_US
dc.subjectyield enhancementen_US
dc.subjectprocess capabilityen_US
dc.subjectAPCen_US
dc.title利用統計方法自動依工程忍受度判斷機台差異及其在半導體製程改善之應用zh_TW
dc.titleA New Statistical Method for Automatic Partitioning Tools According to Engineers’ Tolerance Control in Process Improvementen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
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