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Record W4416880884 · doi:10.37665/smyfsfn12791

Lead-Free Assembly and Qualification of a Storage Class PCBA

2009· article· W4416880884 on OpenAlexaff
Matthew Kelly, Tom Truman, Adzahar Samat, Eric Goh, S.K. Tan, M. Tan, Seung Jin Lee

Bibliographic record

VenueSMTA International · 2009
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsReworkReliability (semiconductor)Surface-mount technologyIBMBall grid arrayQuality (philosophy)PalletProcess (computing)Temperature cycling

Abstract

fetched live from OpenAlex

ABSTRACT Efforts continue to learn more about the quality and reliability performance of Server and Storage class electronic hardware assemblies using new lead-free assembly processes and materials. In this collaborative qualification trial, a low/medium complexity storage class product vehicle was assembled and tested using next generation lead-free assembly materials. The intent of this work was to continue building a reliability performance database for Storage class hardware and to communicate resultant findings to the industry via case study. This paper will discuss the comprehensive qualification trial results of an IBM low/medium complexity tape storage device using a no-clean lead-free assembly process including primary attach SMT reflow, and hot gas BGA rework processes. Of particular interest in this study was the performance of in-circuit test (ICT) using next generation lead-free solders. Voiding performance, effects of multiple heat cycles, and overall ICT yield improvements were assessed. Various tests were conducted to evaluate resultant time zero quality levels of the product vehicle including 5DX-ray, ICT, bulk solder joint formation via cross sectioning, and metallurgical analysis using SEM. Reliability performance of the product vehicle was tested using accelerated thermal cycling (ATC), high temperature storage (HTS), vibration and shock protocols. The materials / processes were assessed using Surface Insulation Resistance (SIR) electromigration testing on a specially designed test card.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.015
GPT teacher head0.258
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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