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
- Bonjun Koo (ORCID: https://orcid.org/0000-0002-8717-5043)
- Seok‐Hwan Huh (ORCID: https://orcid.org/0000-0002-8084-4144)
- Gyu-Hyeong Bak
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