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Three-Stage Optimization of Pre-Bond Diagnosis of TSV Defects

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Abstract

Pre-bond TSV testing and defect identification is important for yield assurance of 3D stacked devices. Building on a recently proposed pre-bond TSV probing procedure, this paper develops a three-stage optimization method named “SOS3” to greatly reduce TSV test time without losing the capability of identifying given number of faulty TSVs. The optimization stages are as follows. First, an integer linear programming (ILP) model generates a near-optimal set of test sessions for pre-bond defective TSV diagnosis. Second, an iterative greedy procedure sequences the application of those test sessions for quicker diagnosis. Third, a TSV defect identification algorithm terminates testing as quickly as possible, often before all sessions are applied. Extensive simulation experiments are done for various TSV networks and the results show that the SOS3 framework greatly speeds up the pre-bond TSV test.

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Acknowledgments

This research was supported in part by the National Science Foundation Grant CCF-1116213.

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Authors and Affiliations

  1. Department of Electrical, Computer Engineering Auburn University, Auburn, AL, 36849, USA

    Bei Zhang & Vishwani D. Agrawal

  2. Apple Inc., Cupertino, CA, 95014, USA

    Bei Zhang

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  1. Bei Zhang
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  2. Vishwani D. Agrawal
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Correspondence to Bei Zhang.

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Responsible Editor: K. K. Saluja

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Zhang, B., Agrawal, V.D. Three-Stage Optimization of Pre-Bond Diagnosis of TSV Defects. J Electron Test 33, 573–589 (2017). https://doi.org/10.1007/s10836-017-5681-x

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  • DOI: https://doi.org/10.1007/s10836-017-5681-x

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