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Record W4416877186 · doi:10.37665/smizngx75093

Critical Manufacturing Issues and Solutions for Tracking Moisture Sensitive Devices (MSDs)

2001· article· W4416877186 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSMTA International · 2001
Typearticle
Language
FieldComputer Science
TopicExperience-Based Knowledge Management
Canadian institutionsCentre Intégré de Santé et Services Sociaux de la Gaspésie
Fundersnot available
KeywordsReliability (semiconductor)Control (management)Tracking (education)Customer satisfactionProduct (mathematics)Material handlingControl systemContainer (type theory)

Abstract

fetched live from OpenAlex

ABSTRACT The control of moisture-sensitive devices (MSDs) prior to SMT reflow is a critical assembly issue that has a direct impact on final product reliability and customer satisfaction as well as manufacturing costs. The guidelines for storage and handling of MSDs are clearly defined in the joint IPC/JEDEC standard J-STD-033. However, the proper identification, logging and date/time calculations have always been very challenging to implement with manual procedures and they are prone to a high level of human errors. In most cases, implementation of an internal manual control procedure requires major simplifications to the industry standard. This results in baking parts that that do not need it while assembling some that should be baked. Both will affect manufacturing and material costs while increasing the risk of early life failures in the field. The solution to address all these issues consists of an automated control system that is both simple-to-use and can insure a very high level of control. The foremost objective of the system is to avoid assembling components that have exceeded their allowable limit. This is achieved by automatically tracking each reel or stack of trays from the time they are removed from their original dry bag until all parts are placed prior to reflow. The second objective is to minimize the number and duration of bake cycles by taking into account all applicable rules from the industry standard and ambient conditions, while providing real-time status and advance warnings of expiration.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.040
GPT teacher head0.330
Teacher spread0.290 · 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