有效过程监控所需的SRAM测试策略的关键属性

J. Khare, S. Griep, H.-D. Oberle, W. Maly, D. Schmitt-Landsiedel, U. Kollmer, D. Walker
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引用次数: 16

摘要

良率学习是保证生产效率的关键过程,必须基于有效的缺陷诊断程序。本文提出了一种这样的方法,利用sram的测量和计算机生成的缺陷-故障字典。讨论的重点是“诊断的解决”,即解决尽可能多的各种缺陷的能力。为了评估分辨率极限,我们进行了一个包含字典生成和SRAM测试的实验。将测试结果与模拟位图进行比较,并使用故障分析分析差异。结果表明,基于仿真的缺陷诊断是非常有效的。如果选择合适的SRAM设计、测试策略和缺陷模型,也可以增强其性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Key attributes of an SRAM testing strategy required for effective process monitoring
Yield learning-a key process in assuring manufacturing efficiency-must be based on effective defect diagnostic procedures. One such procedure, using measurements of SRAMs and a computer-generated defect-fault dictionary, is presented in this paper. The discussion is focused on the 'resolution of diagnosis', which is the ability to resolve as large a variety of defects as possible. To assess the resolution limits, an experiment involving dictionary generation and SRAM testing was conducted. The test results were compared against simulated bitmaps, and the differences were analyzed using failure analysis. The results obtained confirmed that defect simulation-based diagnosis can be very effective. It can also be enhanced if appropriate SRAM designs, testing strategies and defect models are chosen.<>
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