Bibliographic record
Abstract
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 and storage. 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 pSemi for qualification of RFIC packages for wireless, broadband and Automotive 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 on the Board for the IMAPS San Diego Chapter and Vice President of Communications at SMTA San Diego chapter. On Demand Webinar
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.028 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".