Imaps Nw Ness 4 23 03 Compressed

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LTCC Sensitivity Analysis Presentation 2004

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Imaps Nw Ness 4 23 03 Compressed

  1. 1. <ul><li>By </li></ul><ul><li>Eric Ness </li></ul><ul><li>Kyocera America, Inc., LTCC Division </li></ul><ul><li>With contributions from NPD group, KAI </li></ul>Variational Analysis in LTCC Packages
  2. 2. Outline <ul><li>LTCC PROCESS </li></ul><ul><li>TOTAL VARIANCE </li></ul><ul><li>PHYSICAL MEASUREMENTS </li></ul><ul><li>RF MEASUREMENT </li></ul><ul><li>EXAMPLE: DIELECTRIC THICKNESS </li></ul><ul><li>EXAMPLE: RF VIA </li></ul><ul><li>SUMMARY </li></ul>
  3. 3. LTCC Process 1 2 3 <ul><li>Sequential Processes on Individual Layers </li></ul>PUNCH -- VIA FILL -- PRINTING --
  4. 4. LTCC Process <ul><li>Sequential Processes on Multi-Layers </li></ul>Collate Sheets -- 4 Lamination -- 5 Fired Ceramic Multilayer -- 6
  5. 5. LTCC Package cross-section Vias Stacked Vias Internal Conductors Thermal Vias Thick Film Dielectric or Post Fire Resistor Back side or External Conductor Top side or External Conductor Dielectric Layers Buried Resistors
  6. 6. Process Variance <ul><li>Variation is associated with EACH process </li></ul><ul><li>Total Variance is sum of each process variance </li></ul> 2 1 +  2 2 +  2 3 +  2 4 + … =  2 TOTAL <ul><li>Understanding variation key to process control </li></ul><ul><li>Measure, Measure, Measure…… </li></ul>
  7. 7. Single Layer Test Panel
  8. 8. Test Panel Features LOWER LEFT CENTER
  9. 9. Measurement Multi-layer Test
  10. 10. Results: 64 panels measured PROCESS 3  FEATURE PUNCH 0.3 mil PATTERN PRINT 0.5 mil LAMINATION, VIA & PRINT 1.3 mil LAMINATION, CAVITY 2.7 mil FIRING (SHRINKAGE) 0.9 % THICKNESS (SHRINKAGE) 3.4 % SAW CUT 2.2 mil COMPONENT MACHINE 1.6 mil COMPONENT ATTACH 4.0 mil
  11. 11. RF Measurements <ul><li>PHYSICAL VARIATION </li></ul><ul><li>- Measure physical features. </li></ul><ul><li>RF MEASUREMENT VARIATION </li></ul><ul><li>- Repeat measurements on stripline. </li></ul><ul><li>COMBINE THE TWO </li></ul><ul><li>- Add variation to the model. </li></ul><ul><li>- “Monte Carlo” simulation. </li></ul>
  12. 12. RF Stripline Design Calculations (S 21 in dB) <ul><li>S 21L1 = (S 21 /inch)*(L1)+2*S 21  </li></ul><ul><li>S 21L2 = (S 21 /inch)*(L2)+2*S 21  </li></ul>Subtract 2) from 1) cancels 2*S 21  terms and gets… S 21L1 - S 21L2 = (S 21 /inch)*(L1-L2) Solve for S 21 /inch (S 21L1 - S 21L2 )/(L1-L2) = S 21 /inch Measured results  L1 L2
  13. 13. RF Stripline Insertion Loss
  14. 14. Example: Dielectric Thickness 1 2 3 4 5 6 GROUND TAPE DIELECTRIC GROUND PRINTED DIELECTRIC FILTER ELEMENT SONOSCAN IMAGE THROUGH FIRED PART Stripline BandPass Filter for 2.45 GHz
  15. 15. X-section <ul><li>THREE DIELECTRIC </li></ul><ul><li>THICKNESSES </li></ul><ul><li>PRINTED </li></ul><ul><li>MEASUREMENTS </li></ul><ul><li>ON CROSS-SECTION </li></ul><ul><li>PLANNED THICKNESS: </li></ul><ul><li>A -- 15 micron </li></ul><ul><li>B -- 17 micron </li></ul><ul><li>C -- 19 micron </li></ul>Dielectric Thickness  Frequency Response
  16. 16. Comparison with model At 2.45 GHz -2.1 Measured -2.2 HFSS IL (dB) Data
  17. 17. Variation greatest within lot Insertion Loss at 2.45 GHz Avg(6): -2.42 dB Max: -2.04 dB; Filter: A2 Min: -2.81 dB; Filter: A6
  18. 18. Example: RF Via Transition RF VIA RF INPUT (LEAD) SOURCES OF VARIATION <ul><li>PRINT DEFINITION </li></ul><ul><li>OF RF LINE </li></ul><ul><li>VIA ALIGNMENT </li></ul><ul><li>DIELECTRIC THICKNESS </li></ul><ul><li>LEAD ALIGNMENT </li></ul><ul><li>BRAZE FILLET SHAPE </li></ul>
  19. 19. Parameter Measurement <ul><li>Measurements on Cross-Sections Confirm </li></ul><ul><li>Model Assumptions. </li></ul>
  20. 20. Braze Fillet DIELECTRIC THICKNESS VIA ALIGNMENT BRAZE THICKNESS BRAZE FILLET SHAPE
  21. 21. Modeling: Braze Fillet Model rka_123 was modified to include a braze structure observed in cross-sections. Braze Board ceramic Lead Changes: added 2 mils to braze height for total 3 mils, Added 3 mil wide (each side) tapered braze fillets to full height of lead
  22. 22. Variation Added to Model
  23. 23. Modeled Variation in Spec
  24. 24. Summary <ul><li>LTCC packages perform as predicted </li></ul><ul><li>Good prediction requires data: </li></ul><ul><li>- single layer process variation </li></ul><ul><li>- multi-layer process variation </li></ul><ul><li>- accurate parameter measurements </li></ul><ul><li>- incorporation of observed variation </li></ul><ul><li>in RF models </li></ul>

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