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Record W4416882226 · doi:10.37665/ppmajms97441

DOE for Process Validation Involving Numerous Assembly Materials and Test Methods

2009· article· W4416882226 on OpenAlexaff
Renee J. Michalkiewicz, Gaylon Morris, Simin Bagheri

Bibliographic record

VenuePan Pacific Symposium · 2009
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsHain Celestial (Canada)
Fundersnot available
KeywordsReworkPrinted circuit boardSolderingSurface-mount technologyProcess (computing)Solder pasteProcess validationTest method

Abstract

fetched live from OpenAlex

ABSTRACT Selecting products that have been qualified by industry standards for use in printed circuit board assembly processes is an accepted best practice. That products which have been qualified, when used in combinations not specifically qualified, may have resultant properties detrimental to assembly function though, is often not adequately understood. Printed circuit boards, solder masks, soldering materials (flux, paste, cored wire, rework flux, paste flux, etc.), adhesives, and inks, when qualified per industry standards, are qualified using very specific test methods which may not adequately mimic the assembly process ultimately used. It is recommended that products used in combination on a printed circuit assembly be qualified in combination to the extent necessary to provide a full understanding of interactions that may occur in the product. IPC J-STD-001 provides good guidance with regards to process validation testing although said testing is limited to the Appendix of the document. J-STD-001D, Appendix C focuses on process validation via Surface Insulation Resistance (SIR) Testing. The limitation to relying solely on SIR testing is its inherent inability to detect possible assembly issues which could result from employed combinations of printed circuit boards, solder masks, soldering materials (flux, paste, cored wire, rework flux, paste flux, etc.), adhesives, and inks. The authors’ intention with this paper is to describe two Designs of Experiments (DOE’s) that were developed for process validation. The first relies on SIR testing as the sole means of qualifying the final assembly. The second explores the use of a broad range of tests chosen to closely represent the end use application. DOE #1 was based upon the SIR testing procedure as per ANSI/J-STD-004, IPC-TM-650 2.6.3.3A the method which is also specified in J-STD-001. The scope of the test method is to determine the degradation of electrical insulation resistance of PCB specimens after exposure to specified materials. Since during the normal manufacturing process, a board assembly is exposed to a number of chemicals, for this DOE the standard SIR test coupons were prepared in such a way as to mimic a “typical” chemical mix that a board assembly may come in contact with during assembly. This involved applying the appropriate chemicals in the typical process order using appropriate process conditions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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 designBench or experimental
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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