Using FEA to determine test speed for high speed shear test on BGA based on field conditions
Bibliographic record
Abstract
Miniaturization and increased functionality has been the trend in the mobile electronic device industry. Inevitably, the drive for increased density of miniaturized components has led to the miniaturization of the BGA joints. Smaller joints, in general, have shorter lives as the crack propagation path is shorter. The high speed shear test is gaining popularity as a component-level test to ensure good outgoing solder joints. One advantage of this test over the static shear test is that higher test speeds induce brittle failure in the intermetallic layer (IMC) of the joint, similar to that in drop impact. As a result, this test can detect variations in substrate finishing quality and joint reflow conditions that could lead to premature drop impact failures. However, selection of test speed is critical. The general consensus is to test at the speed where IMC failures are induced. With recent advances in pad finishing and solder alloys resulting in thinner and more uniform IMC layers, testing at a speed where IMC failures occur could result in over-testing the device, well beyond the strain rates experienced in the field. This, in turn, would lead to the over-design of solder joints. Clearly, a method to determine equivalent shear test speed is required, where strain rates during shear test are matched to that in field conditions. This work presents a methodology to determine the equivalent shear test speed for high speed shear test based on shock and vibration requirements. FEA is used to match the maximum strain rates during the most severe impact or vibration application of the device to that during high speed shear test. Usage of the methodology is demonstrated on a board with a BGA component under three different drop conditions. Results show that for the three drop conditions, the equivalent shear speed is lower than 200mm/s. Given that the maximum capability of the tester is 4m/s, shear speed for high speed shear test needs to be selected carefully.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".