Residual Stress Correlation to ATC Reliability Scale in the μPGA-Solder Joint-PCB Pad System*
Bibliographic record
Abstract
ABSTRACT Mechanical stresses from various force fields are a major concern for solder joint reliability. Instantaneous failure on components such as BGA with Electroless Nickel Immersion Gold (ENIG) substrate metallization interconnects to solder joint, under large deflection and high strain rate, occurs when an uncontrollable source is imposed. The generally accepted resolution approach consists of reducing this impact but offers no physical basis with regards to solder joint reliability. Instead, this reduction strategy may simply shift the failure mode from instantaneous failure to early fatigue failure due to the residual stress. In this study, mechanical stress is exerted onto a μPGA-compliance pin-Solder bump-PCB Pad interconnect system on a test board by Four-Point-Bending. Loading speed and deflection are used as the control parameters to derive the residual stress correlation to the reliability scale. First, the critical instantaneous loading strain rate and deflection (Kcr) is derived by real-time monitoring of resistance in daisy chain, loading speed & deflection in tensile tester, and strain in gages mounted to the test PCB. Then multiple percentages of the critical Kcr are applied to the interconnect system. Finally, the residue stress affected test board is tested in the Accelerated Temperature Cycling (ATC) oven and failure cycle and failure mode are analyzed. Early failures of the high loading speed and deflection affected μPGA-Solder Joint-PCB Pad systems were observed after 1500 ATC reliability testing. Both interfacial failures at pin to solder joint and pad lifting were observed in the system. This finding proved our hypothesis presented at 2002 that residual stress would reduce the fatigue life of interconnect bonding to package substrate and PCB pad. Empirical fatigue life N-residual strain e relationship shows logical inference to the crack propagation either in transgranular or intergranular fracture mode. The empirical fatigue life projection methodology is proposed. Both mathematical and graphic solutions are derived based on the empirical approach. The practical mechanical process parameters, loading speed and deflection are able to link to the fatigue life. Three process steps, forward fatigue life prediction & residual stress reduction, backward process improvement and tooling re-design by loading speed and deflection, and long term process control and management are proposed and implemented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".