Investigation of a connector electrical failure
Bibliographic record
Abstract
Abstract A PC product built by Celestica experienced a high rate of functional failure. Failure was associated with the CPU and CPU connector (known as a zero insertion force, ZIF type) since mechanically flexing the CPU stack induced failure. This problem became particularly serious when the customer adopted an uncontrolled (manual) “press” test, resulting in a large amount of rejected product which may have been functional under normal operating conditions. A failure analysis method involving static loading the CPU and epoxy potting the connector stack was developed to mechanically “trap” the fail condition. Sectioning and electrical probing was used to determine which of the 240 active connector pins have high resistance. Analysis of suspect connector pins and contact surfaces pointed to several possible causes of failure. SEM‐EDX revealed localized damage to the Au plating with exposed Ni and NiO. XPS and TOF‐SIMS with depth profiling confirmed the presence of a ∼100 nm layer of a fluorocarbon on the Au surface. Although it was not possible to clearly locate the individual electrical contact spots (1–10 µm diameter) to identify localized contamination, the presence of a probable insulating coating was sufficient evidence to follow‐up with the connector supplier. The connector spring contacts were found to be coated with an “anti‐flux” agent to prevent wicking of liquid solder onto contact surfaces during the wave solder assembly process. The corrective action was to change the ZIF connector to a type without anti‐flux coating and the failure rate was significantly reduced. Copyright © 2010 John Wiley & Sons, Ltd.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".