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BIST Methodology, Architecture and Circuits for Pre-Bond TSV Testing in 3D Stacking IC Systems

BIST Methodology, Architecture and Circuits for Pre-Bond TSV Testing in 3D Stacking IC Systems
Wang, ChaoZhou, JunWeerasekera, RoshanZhao, BinLiu, XinRoyannez, PhilippeJe, Minkyu
DGIST Authors
Je, Minkyu
Issued Date
Article Type
3D ICBISTBuilt-In Self TestDesign for TestabilityDFTElectronics PackagingFunctional CircuitsIntegrated Circuit InterconnectsIntegrated Circuit TestingNetwork ArchitecturePre-Bond TSV TestingRobustness AnalysisSanitary SewersState-of-Art MethodsStuck-at Fault TestsSubstrate ResistanceSwitching CircuitsThree Dimensional Integrated CircuitsThrough-Silicon-ViasTSV
This paper presents a built-in self test (BIST) methodology, architecture and circuits for testing Through Silicon Vias (TSVs) in 3D-IC systems prior to stacking in order to improve 3D-IC yield and reduce overall test cost. A scan switch network (SSN) architecture is proposed to perform pre-bond TSV scan testing in test mode, and operate as functional circuit in functional mode, respectively. In the SSN, novel test structures and circuits are proposed to address pre-bond TSV test accessibility issue and perform stuck-at-fault tests and TSV tests. By exploiting the inherent RC delay characteristics of TSV, a novel delay-based TSV test method is also proposed to map the variation of TSV-to-substrate resistance due to TSV defects to a test path delay change. Compared with state-of-art methods, the proposed BIST methodology addresses pre-bond TSV testing with a low-overhead integrated test solution which is compatible to existing 2D-IC testing method. The proposed BIST architecture and method can be implemented by standard DFT design flow and integrated into a unified pre-bond TSV test flow. Experiment results and robustness analysis are presented to verify the effectiveness of the proposed self-test methodology, architecture, and circuits. © 2004-2012 IEEE.
Institute of Electrical and Electronics Engineers Inc.
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Department of Electrical Engineering and Computer Science IMPACT Lab 1. Journal Articles


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