標題: A Novel Statistical Method for Automatically Partitioning Tools According to Engineers' Tolerance Control in Process Improvement
作者: Tu, Kevin Kai-Wen
Lee, Jack Chao-sheng
Lu, Henry Horng-Shing
統計學研究所
資訊管理與財務金融系 註:原資管所+財金所
Institute of Statistics
Department of Information Management and Finance
關鍵字: APC;Bayesian fit;CART;C-p;C-pk;data mining;process capability;reversible jump Markov chain Monte Carlo;yield enhancement
公開日期: 1-八月-2009
摘要: In the semiconductor industry, tool comparison is a key task in yield or product quality enhancements. We develop a new method to automatically partition tools. The new method is called tolerance control partitioning (TCP). The advantages of TCP include 1) taking into account of unbalanced tool usage in manufacturing processes; 2) further partitioning these tools into several homogenous groups by related metrology results instead of detecting only the significant difference; and 3) partitioning these tools according to engineers' tolerance controls to avoid too many groups with small differences. TCP also could be applied in all similar cases such as experimental recipe or material comparisons. Therefore, using TCP, engineers could speed up yield or product quality ramping. Two simulation cases illustrate the advantages of TCP method. We also applied TCP to two real cases for yield and Cp/Cpk enhancement in the semiconductor industry. The results confirm the practical feasibility of this method.
URI: http://dx.doi.org/10.1109/TSM.2009.2025812
http://hdl.handle.net/11536/6881
ISSN: 0894-6507
DOI: 10.1109/TSM.2009.2025812
期刊: IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING
Volume: 22
Issue: 3
起始頁: 373
結束頁: 380
顯示於類別:期刊論文


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