Stress-Strength Interference Model for the Optimization of Test Coupon Engineering for Microvia Reliability

The demand in the automobile electronic industry for compact printed circuit boards requires highly reliable microvias that work as an interconnect among the conducting layers of printed circuit boards. To meet industry needs, researchers have developed different testing coupons to capture the early failure of microvias using accelerated testing. However, the percentage of failing microvias is insignificant when considering the failure phenomenon. It highlights the need for a statistical model that can give a significant likelihood of failure microvias that can be reviewed for reliability studies. In this paper, we have developed a statistical test model of microvia using the stress-strength interference method to enhance the possibility of microvia failure to investigate the phenomenon of failure during thermomechanical loading. Finite element models were developed using the design of the experiment technique using the Taguchi method. The results showed a 12% increase in the probability of microvia failure, providing sufficient room to find the behavior of microvias that fail. Moreover, the simulation modeling results correlate with the literature models to verify the accuracy of the model.

Authors

Institutions

Publication Details

Journal
IEEE Open Journal of Power Electronics
Published
2025-01-01
DOI
https://doi.org/10.1109/ojpel.2025.3584263
Citations
1
Primary Topic
Electronic Packaging and Soldering Technologies
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stress-Strength Interference Model for the Optimization of Test Coupon Engineering for Microvia Reliability

Heba G. Mohamed, Michael Haider, Syed Mujahid Abbas, Wahaj Abbas Awan
1 citations
IEEE Open Journal of Power Electronics
Electronic Packaging and Soldering Technologies
0.73
article

Stress-Strength Interference Model for the Optimization of Test Coupon Engineering for Microvia Reliability

Heba G. Mohamed, Michael Haider, Syed Mujahid Abbas, Wahaj Abbas Awan
article en
1 citations

Abstract

The demand in the automobile electronic industry for compact printed circuit boards requires highly reliable microvias that work as an interconnect among the conducting layers of printed circuit boards. To meet industry needs, researchers have developed different testing coupons to capture the early failure of microvias using accelerated testing. However, the percentage of failing microvias is insignificant when considering the failure phenomenon. It highlights the need for a statistical model that can give a significant likelihood of failure microvias that can be reviewed for reliability studies. In this paper, we have developed a statistical test model of microvia using the stress-strength interference method to enhance the possibility of microvia failure to investigate the phenomenon of failure during thermomechanical loading. Finite element models were developed using the design of the experiment technique using the Taguchi method. The results showed a 12% increase in the probability of microvia failure, providing sufficient room to find the behavior of microvias that fail. Moreover, the simulation modeling results correlate with the literature models to verify the accuracy of the model.

IEEE Open Journal of Power ElectronicsVol. 6
Princess Nourah bint Abdulrahman University (SA), Incheon National University (KR), Chungbuk National University (KR), Yokohama National University (JP)
Openalex Percentile: Top 27%
Electronic Packaging and Soldering Technologies
0.73
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.