Spatial stochastic processes for yield and reliability management with applications to nano electronics
Spatial stochastic processes for yield and reliability management with applications to nano electronics
复制标题
用于产量和可靠性管理的空间随机过程及其在纳米电子学中的应用
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Jung Yoon Hwang
中科院分区：
文献类型：
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作者：
Jung Yoon Hwang
成品率和可靠性管理的空间随机过程及其在纳米电子学中的应用。（2004年12月）Jung Yoon Hwang，B.A.，韩国军事学院，德克萨斯A&M大学咨询委员会主席：Way Kuo博士这项研究使用晶圆上缺陷的空间特征来检查半导体制造过程中工艺变化的检测和控制。将空间随机过程应用于半导体成品率建模和外部可靠性估计模型。建立了基于空间点工艺的集成电路成品率模型。根据晶片上的位置变化的缺陷密度的空间非均匀泊松过程建模。并且，为了捕捉晶片之间的缺陷图案的变化，应用随机系数模型和基于模型的聚类。基于模型的聚类也被应用到制造过程控制中，用于检测由可分配原因产生的这些缺陷簇。在新的成品率模型的基础上，建立了基于缺陷数据的外部可靠性模型和统计缺陷增长模型。
Spatial Stochastic Processes for Yield and Reliability Management with Applications to Nano Electronics. (December 2004) Jung Yoon Hwang, B.A., Korea Military Academy; M.S., Texas A&M University Chair of Advisory Committee: Dr. Way Kuo This study uses the spatial features of defects on the wafers to examine the detection and control of process variation in semiconductor fabrication. It applies spatial stochastic process to semiconductor yield modeling and the extrinsic reliability estimation model. New yield models of integrated circuits based on the spatial point process are established. The defect density which varies according to location on the wafer is modeled by the spatial nonhomogeneous Poisson process. And, in order to capture the variations in defect patterns between wafers, a random coefficient model and model-based clustering are applied. Model-based clustering is also applied to the fabrication process control for detecting these defect clusters that are generated by assignable causes. An extrinsic reliability model using defect data and a statistical defect growth model are developed based on the new yield model.