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Record W4416884956 · doi:10.37665/srjctkd92816

A Parametric Approach To Optimizing BGA Design for Reflow Reliability

2011· article· W4416884956 on OpenAlexaff
Alireza Sahami Shirazi, Hua Lu, A. Varvani‐Farahani

Bibliographic record

VenueSoldering and Reliability Conferences · 2011
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBall grid arrayReliability (semiconductor)Parametric statisticsProcess (computing)Surface-mount technologyDimension (graph theory)Printed circuit boardGridParametric model

Abstract

fetched live from OpenAlex

ABSTRACT Thermal warpage is a keen reliability concern for BGA (Ball Grid Array) and surface mounted PCBA (Printed Circuit Board Assembly). The authors previously proposed a hybrid method that correlates analytically modeled and directly measured warpage for a real package. While iteratively reaching the high correlation, the accuracy of the input material properties is simultaneously improved. An application of the model to a specific package is basically a model refining and verification process which ensures a high confidence level of the final modeling output such as the stresses/strains along the adhesive interfaces and the package warpage. Given that the output parameters are expressed as functions of temperature, geometric dimension and materials’ properties, the approach enables a quick, quantitative and full scale evaluation of the package’s performance. This paper presents an application example to illustrate how the method is executed in a package performance evaluation and prediction and how the evaluation facilitates the package design and manufacturing for reliability.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.435
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.256
Teacher spread0.178 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2011
Admission routes1
Has abstractyes

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