基于在线缺陷测量估计良率的局限性

S. Riley
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引用次数: 3

摘要

为了根据在线缺陷测量的数据估计良率损失,必须做出某些假设,以便使数据适合给定的良率模型。为了使假设可信,必须理解和处理由于检测、审查抽样和分类分组而产生的固有限制。方法,如在线测量数据的相关性,测试数据可以被误解,如果问题,如多次失效的模具不考虑。本文讨论了在线测量的一些固有局限性,以及它们如何影响产量估计的预期结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Limitations to estimating yield based on in-line defect measurements
To estimate yield loss based on data from in-line defect measurements, certain assumptions must be made so the data can be made to fit a given yield model. For the assumptions to be credible, inherent limitations due to detection, review sampling, and classification groupings must be understood and dealt with. Methodologies such as correlations of in-line measurement data to test data can be misinterpreted if issues such as multiple-failed die are not considered. This paper discusses some of the inherent limitations of in-line measurements and how they can affect the intended outcome of yield estimations.
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