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Record W4416879640 · doi:10.37665/wexqsnw70661

Practical Guidelines in Handling Moisture Sensitivity of SMT Packages

2016· article· W4416879640 on OpenAlexaboutno aff
Mumtaz Y. Bora

Bibliographic record

VenueOn-Demand Webinars · 2016
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsIBMStandardizationAutomotive industrySurface-mount technologyProduct (mathematics)Integrated circuit packagingCleanroomProcess (computing)

Abstract

fetched live from OpenAlex

ABSTRACT Handling of moisture sensitive packages is an ongoing learning process in volume manufacturing. Improperly handled and stored MSDs can impact yields and reliability. The presentation will cover a review of the industry standards for MSDs (J-STD-020, J-STD 033 and J-STD 075) and their applications in moisture control. PWBs used for assembly also require controlled storage and handling. Board surface finishes, storage and baking guidelines will be reviewed per the IPC 1601 standard. Handling of MSDs from receipt to use at reflow will be reviewed, including practical guidelines in labeling, tracking, packing, storage and supplier audits. About the Presenter: Mumtaz Y. Bora has a B.S. in Chemistry and Material Sciences from University of Mumbai, India and University of Ottawa, Canada. She has a Master of Science in Interactive Telecommunications from University of Redlands, California. She has over 25 years of PWB, SMT assembly and advanced packaging development experience at IBM Endicott and IBM Austin, TX. She has worked in new product development, and qualification of high volume handset assemblies at Qualcomm and Kyocera-Wireless Corporation. She has worked with suppliers and subcontractors in several parts of Asia. She is currently a Sr. Staff Packaging Engineer at Peregrine Semiconductor for qualification of RFIC packages for wireless, broadband Automotive and Hi-Rel/Space applications. She is a member of IPC standardization committees and contributes to the standards development. She has 16 publications and 3 patents. She is the Past President of the SMTA San Diego chapter and Co-chair of the Moisture Sensitive Devices Council. She is currently President of the IMAPS San Diego Chapter and Vice President of SMTA San Diego chapter. On Demand Webinar

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)0.008
metaresearch head score (Gemma)0.020
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: Methods · Consensus signal: Methods
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0200.030

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 head0.032
GPT teacher head0.305
Teacher spread0.273 · 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
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
Published2016
Admission routes1
Has abstractyes

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