Efficient Wafer-level Spatial Variation Modeling for Multi-site RF IC Testing

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Riaz-ul-haque MIAN, Tomoki NAKAMURA, Masuo KAJIYAMA, Makoto EIKI, Michihiro SHINTANI
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引用次数: 0

Abstract

Wafer-level performance prediction techniques have been increasingly gaining attention in production LSI testing due to their ability to reduce measurement costs without compromising test quality. Despite the availability of several efficient methods, the site-to-site variation commonly observed in multi-site testing for radio frequency circuits remains inadequately addressed. In this manuscript, we propose a wafer-level performance prediction approach for multi-site testing that takes into account the site-to-site variation. Our proposed method is built on the Gaussian process, a widely utilized wafer-level spatial correlation modeling technique, and enhances prediction accuracy by extending hierarchical modeling to leverage the test site information test engineers provide. Additionally, we propose a test-site sampling method that maximizes cost reduction while maintaining sufficient estimation accuracy. Our experimental results, which employ industrial production test data, demonstrate that our proposed method can decrease the estimation error to 1/19 of that a conventional method achieves. Furthermore, our sampling method can reduce the required measurements by 97% while ensuring satisfactory estimation accuracy.
多站点射频集成电路测试的高效晶圆级空间变化建模
由于能够在不影响测试质量的情况下降低测量成本,晶圆级性能预测技术在生产LSI测试中越来越受到关注。尽管有几种有效的方法,但在射频电路的多站点测试中通常观察到的站点到站点的变化仍然没有得到充分解决。在这篇论文中,我们提出了一种多站点测试的晶圆级性能预测方法,该方法考虑了站点到站点的变化。我们提出的方法建立在高斯过程(一种广泛使用的晶圆级空间相关建模技术)的基础上,并通过扩展分层建模来利用测试工程师提供的测试场地信息来提高预测精度。此外,我们提出了一种测试现场抽样方法,在保持足够估计精度的同时最大限度地降低成本。采用工业生产试验数据的实验结果表明,该方法可以将估计误差降低到传统方法的1/19。此外,我们的采样方法可以在保证满意的估计精度的同时减少97%的所需测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.10
自引率
20.00%
发文量
137
审稿时长
3.9 months
期刊介绍: Includes reports on research, developments, and examinations performed by the Society''s members for the specific fields shown in the category list such as detailed below, the contents of which may advance the development of science and industry: (1) Reports on new theories, experiments with new contents, or extensions of and supplements to conventional theories and experiments. (2) Reports on development of measurement technology and various applied technologies. (3) Reports on the planning, design, manufacture, testing, or operation of facilities, machinery, parts, materials, etc. (4) Presentation of new methods, suggestion of new angles, ideas, systematization, software, or any new facts regarding the above.
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