An MIV Fault Diagnosis Method Based on Signal Transmission Performance Analysis

Monolithic inter-tier vias (MIVs) in monolithic 3-D integrated circuits (M3D ICs) enables massive vertical integration. However, MIVs are more susceptible to defects due to high integration density and complex manufacturing processes. Existing MIV test techniques can effectively detect and locate MIV faults, but diagnosable fault types are limited. We propose a novel fault diagnosis method based on signal transmission performance analysis. This method can diagnose more fault types, including resistive open, hard open, short, and leakage faults. In the proposed solution, fault diagnosis can be carried out by comprehensively monitoring voltage and delay characteristics of MIVs. The effectiveness of fault diagnosis is verified through high speed simulation program with integrated circuit emphasis (HSPICE) simulations. We also perform Monte Carlo simulations to prove that the proposed method has high robustness even in the case of process variations. Experimental results show that the proposed method has low hardware overhead while ensuring high diagnostic resolution.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Published
2024-12-27
DOI
https://doi.org/10.1109/tvlsi.2024.3518554
Citations
2
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.70

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An MIV Fault Diagnosis Method Based on Signal Transmission Performance Analysis

Cuiyu Liu, Yang Yu, Ziwen Xiao, Lifu Du et al.
2 citations
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Industrial Vision Systems and Defect Detection
0.70
article

An MIV Fault Diagnosis Method Based on Signal Transmission Performance Analysis

Cuiyu Liu, Yang Yu, Ziwen Xiao, Lifu Du, Zhiming Yang
article en
2 citations

Abstract

Monolithic inter-tier vias (MIVs) in monolithic 3-D integrated circuits (M3D ICs) enables massive vertical integration. However, MIVs are more susceptible to defects due to high integration density and complex manufacturing processes. Existing MIV test techniques can effectively detect and locate MIV faults, but diagnosable fault types are limited. We propose a novel fault diagnosis method based on signal transmission performance analysis. This method can diagnose more fault types, including resistive open, hard open, short, and leakage faults. In the proposed solution, fault diagnosis can be carried out by comprehensively monitoring voltage and delay characteristics of MIVs. The effectiveness of fault diagnosis is verified through high speed simulation program with integrated circuit emphasis (HSPICE) simulations. We also perform Monte Carlo simulations to prove that the proposed method has high robustness even in the case of process variations. Experimental results show that the proposed method has low hardware overhead while ensuring high diagnostic resolution.

IEEE Transactions on Very Large Scale Integration (VLSI) SystemsVol. 33(4)
Harbin Institute of Technology (CN), China Academy of Launch Vehicle Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 24%
Industrial Vision Systems and Defect Detection
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An MIV Fault Diagnosis Method Based on Signal Transmission Performance Analysis — Cuiyu Liu, Yang Yu, et al. · IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2024) | TGRS Research Map | TGRS