Failure Mechanism of Mouse-bite Defects on Printed Circuit Boards and their Detection by Normalized R

Purpose: To identify the failure mechanism of mouse-bite defects and test a detection method that uses 4-wire resistance measurements at the location of the defect.BR/Methods: The failure of circuit boards due to mouse-bite defects was analyzed based on an electronic component failure analysis procedure. The hypothesis was then verified by finite element analysis and a reproducible reliability test. The normalized R, which normalizes the circuit resistance values to detect mouse-bite defects, was calculated and the probability distribution of the circuits was shown. The probability distribution including mouse-bite defects was visualized to distinguish the fault-free circuits from those above the 3-sigma upper limit.BR/Results: Failure mechanisms for mouse-bite defects can include increased resistance in localized areas of the circuit. This leads to Joule heating at the mouse-bite defects. Because of the mismatch in the coefficient of thermal expansion between the copper and dielectric materials, mechanical stress can be concentrated at these sites, leading to cracking. Mouse-bite defects were defined as those with a circuit width of 4 mm or less, and a circuit thickness of 7 mm or less, based on the failure analysis results. These defects were confirmed to cause open-circuit failures under use conditions. Successful detection of mouse-bite defects was confirmed based on a 3-sigma upper limit of the Normalized R metric.BR/Conclusion: By defining the failure mechanism of the mouse-bite defects, we confirmed the possibility of detecting these sites using a 3-sigma upper limit based on the Normalized R metric measured with a 4-wire ohmmeter.

Authors

Publication Details

Journal
Journal of Applied Reliability
Published
2024-12-31
DOI
https://doi.org/10.33162/jar.2024.12.24.4.368
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Failure Mechanism of Mouse-bite Defects on Printed Circuit Boards and their Detection by Normalized R

Bonjun Koo, Seok‐Hwan Huh, Gyu-Hyeong Bak
2 links
Journal of Applied Reliability
Industrial Vision Systems and Defect Detection
article

Failure Mechanism of Mouse-bite Defects on Printed Circuit Boards and their Detection by Normalized R

Bonjun Koo, Seok‐Hwan Huh, Gyu-Hyeong Bak
article en

Abstract

Purpose: To identify the failure mechanism of mouse-bite defects and test a detection method that uses 4-wire resistance measurements at the location of the defect.BR/Methods: The failure of circuit boards due to mouse-bite defects was analyzed based on an electronic component failure analysis procedure. The hypothesis was then verified by finite element analysis and a reproducible reliability test. The normalized R, which normalizes the circuit resistance values to detect mouse-bite defects, was calculated and the probability distribution of the circuits was shown. The probability distribution including mouse-bite defects was visualized to distinguish the fault-free circuits from those above the 3-sigma upper limit.BR/Results: Failure mechanisms for mouse-bite defects can include increased resistance in localized areas of the circuit. This leads to Joule heating at the mouse-bite defects. Because of the mismatch in the coefficient of thermal expansion between the copper and dielectric materials, mechanical stress can be concentrated at these sites, leading to cracking. Mouse-bite defects were defined as those with a circuit width of 4 mm or less, and a circuit thickness of 7 mm or less, based on the failure analysis results. These defects were confirmed to cause open-circuit failures under use conditions. Successful detection of mouse-bite defects was confirmed based on a 3-sigma upper limit of the Normalized R metric.BR/Conclusion: By defining the failure mechanism of the mouse-bite defects, we confirmed the possibility of detecting these sites using a 3-sigma upper limit based on the Normalized R metric measured with a 4-wire ohmmeter.

Journal of Applied ReliabilityVol. 24(4)
Openalex Percentile: Top 63%
Industrial Vision Systems and Defect Detection
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.