Improvements in Decision Making Criteria for Thermal Warpage*

Transcription

1 Improvements in Decision Making Criteria for Thermal Warpage* Neil Hubble Director of Engineering *Originally published in imaps Device Packaging 2016 Thermal Warpage & Strain Metrology

2 Concept Overview Warpage references the flatness or planarity of a surface with respect to a change in temperature Flatness is critical for attachment of surface mount devices Die Board Non Wet Open Head on pillow Stretched joint Head-on-Pillow Open Bridging/Shorts 2

3 How to turn this Concept Overview high low Into a decision based on warpage Pass Fail Warning 3

4 Concept Overview Pass Fail Warning Currently decisions are made on: Visual inspection Or, more commonly, a numerical gauge, typically Signed Warpage Signed Warpage = -67 microns 4

5 Signed Warpage Gauge for Quantitative Decision Making Weaknesses of current industry standard gauge Improved gauge for signed warpage Confusion with Changing Warpage Sign Dual Surface Analysis Signed Warpage Signal Strength Gauge 3D Surface Shape Naming Overview *All data sets are Least Square Fit (LSF) Rotated and real surface shapes unless otherwise stated 5

6 Signed Warpage Industry Standard Uses normalized diagonal lines (ends to 0) AB max + AB min + CD max + CD min Signed Warpage = Coplanarity (max-min) of full surface With pos. or neg. added to coplanarity depending on AB/CD equation 6

7 Signed Warpage Weakness 1 Areas of the sample surface outside of the diagonal lines are not considered when deciding the direction of warpage Side areas not considered for sign decision 7

8 Signed Warpage Weakness 2 The gauge is highly sensitive to measurement noise or local height features since the equation is based on 4 single data points Depth of local feature highly affects calculation 8

9 Signed Warpage Weakness 3 The gauge calculation fails if corner data is not included in the data set, since the diagonal lines cannot be normalized Gauge Fails 9

10 Full Field Signed Warpage (JFFSW) Base warpage sign on 2 nd order polynomial fit of full data set z = a + bx + cy + dxy + ex 2 + fy 2 10

11 Full Field Signed Warpage (JFFSW) JFFSW defined by x 2 and y 2 coefficients and size of the sample in x and y (m by n): -(em 2 + fn 2 ) Addresses issues with Signed Warpage standard JFFSW considers all areas in the data set and not just the diagonals of the surface JFFSW final results are calculated based on a surface fit of the entire data set and are not highly influenced by spikes in the data Abnormal shapes or areas of missing data pose no problem for JFFSW to define positive or negative warpage direction 11

12 Common Confusions with Changing Warpage Sign 12

13 Common Confusions with Changing Warpage Sign Visual inspection of the 3D renderings indicates nearly identical shape However, both Signed Warpage and JFFSW gauges lead the user to believe the plots could be different by as much as 200 microns Solutions still to come 13

14 Dual Surface Analysis The optimal solution for decision making based on analysis of surface mount warpage Consider both sides of attaching interfaces and sign of warpage for each surface no longer matters, only gap in the interface between the two surfaces 14

15 Dual Surface Analysis Decision making criteria can be made purely on maximum and average gap gauge information What if the company only makes components? Previous technical discussions have covered dual surface analysis 15

16 Signal Strength for Signed Warpage JFFSW (microns) Temperature ( C): Sample: Side: BGA 1 Attach Signal Strength: -46% -57% -69% -73% -79% -81% -77% -71% -72% -57% -23% BGA 2 Attach Signal Strength: -44% -60% -65% -67% -71% -72% -75% -77% -52% -42% 5% 16

17 Signal Strength for Signed Warpage Can be applied to either Signed Warpage or JFFSW gauges For Signed Warpage, Signal Strength (SS) For JFFSW, Signal Strength (SS) Adds additional quantitative value to prevent confusion with sudden changes in warpage sign Signal Strength results to be shown on further real world examples during discussion of shape naming

18 Naming of 3D Surface Shapes Shape naming compliments and takes concept of Signal Strength further to classify 3D surfaces into specific name categories Based on 2 nd order polynomial data z = a + bx + cy + dxy + ex 2 + fy 2 Consider e, f, and potentially d coefficients Surfaces with the same shape types would generate smaller gaps Some shape types would fit better with some types and not others

19 Naming of 3D Surface Shapes Coordinate System Consider corner A to be (0,0)

20 Naming of 3D Surface Shapes Considering only e and f coefficients for now

21 Naming of 3D Surface Shapes Practical Example 1 What would you name this shape? JFFSW: +244 microns e: (Note that coefficients units are mils) f: m: 170 n: 170 Signal Strength: % (This is possible because the real surface is being approximated by a 2 nd order surface fit.)

22 Naming of 3D Surface Shapes Practical Example 1 What would you name this shape? Dome or Y-Pipe? Critical ratio:

23 Naming of 3D Surface Shapes Practical Example 2 What would you name this shape? JFFSW: +99 microns e: f: m: 170 n: 170 Signal Strength: 1.67%

24 Naming of 3D Surface Shapes Practical Example 2 What would you name this shape? X-Saddle or Planar/Complex e and f have opposite sign and similar magnitude, (not Pipe, Bowl, or Dome) Critical Ratio:

25 Naming of 3D Surface Shapes Practical Example 3 What would you name this shape? JFFSW: -110 microns e: f: m: 50 n: 50 Signal Strength: 13.36%

26 Naming of 3D Surface Shapes Practical Example 3 What would you name this shape? Planar/Complex Critical Ratio: Surface has recognizable shape, suggesting more naming conventions could be established (perhaps considering 3 rd order polynomial for this case)

27 Naming of 3D Surface Shapes Definitions Consider the previous examples and others the following logic was established experimentally Order of the logic needs to be considered If then shape is Planar/Complex, if not then classify as follows

28 Naming of 3D Surface Shapes Definitions Algorithms are experimentally determined and can be easily adjusted based on industry feedback, with the goal being to normalize qualitative decision making

29 Naming of 3D Surface Shapes Definitions Naming categories can be visually represented on an x/y coordinate system The 8 transitions between pipes and bowl/domes can be shown graphically to better understand the relationships

30 Naming of 3D Surface Shapes Shape Transitions -Y Pipe to Bowl Bowl to -X Pipe -X Pipe to X Saddle X Saddle to +Y Pipe *Artificially Created

31 Naming of 3D Surface Shapes Shape Transitions +Y Pipe to Dome Dome to +X Pipe +X Pipe to Y Saddle Y Saddle to -Y Pipe *Artificially Created

32 Naming of 3D Surface Shapes Factoring Twist More shape names could certainly be defined but where does added complexity overcome further defined naming in terms of value add Factoring the twist of a surface would be one of these categories As we are only considering shape changes along the x and y axis in the data set this suggests that the xy term with the d coefficient would represent a twist factor As before real world examples are considered

33 Naming of 3D Surface Shapes Practical Example 4 What would you name this shape? JFFSW: -227 microns e: f: d: m: 296 n: 296 Signal Strength: 25.79%

34 Naming of 3D Surface Shapes Practical Example 4 What would you name this shape? With positive e and f terms and low signal strength previous definitions would define this shape as complex/planar. However, there is a ratherdistinct shape to the data set. Critical ratio considering twist:

35 Naming of 3D Surface Shapes Practical Example 5 What would you name this shape? JFFSW: -70 microns e: f: d: m: 296 n: 296 Signal Strength: 35.56%

36 Naming of 3D Surface Shapes Practical Example 5 What would you name this shape? Bowl, (just barely) by current standards Critical ratio considering twist:

37 Naming of 3D Surface Shapes Factoring Twist Equation used to label a shaped as twisted Can further specify direction of twist effect by considering whether d is positive or negative d = d = Planar Complex, CD Twist Bowl, AB Twist

38 Naming of 3D Surface Shapes Why Do I Care? Consider placing one of the two surfaces below on top of the other with no flipping or rotation The surfaces have the same X/Y size and are plotted on the same scale The samples have both the same warpage sign and similarly low signal strength Quantitative factors indicate good matching between the surfaces, but it can be seen spatially that these two surfaces would not mate together well

39 Naming of 3D Surface Shapes Why Do I Care? Using Dual Surface Analysis Gap 3D plot Gap 2D Diagonal Max Gap = 366 microns Surface Mount Defect

40 Naming of 3D Surface Shapes Why Do I Care? If we artificially rotated one surface 90 (changing the shape name) Gap 3D plot Gap 2D Diagonal Max Gap = 116 microns Good Attach

41 Conclusions Industry standard for Signed Warpage gauge needs to be updated, and JFFSW has already been adopted as a best practice by many industry leaders Simplifying 3D shapes into a single value can lead to confusion Dual Surface analysis is the optimal approach, but not always practical Adding a signal strength gauge to compliment Signed Warpage would limit confusion with changing sign 3D surfaces can be categorized mathematically into specific shape names to compliment decision making

42 Future Steps The presented material established baseline concepts for improvements in quantifying surface warpage Further case studies and feedback from the industry is needed to: Validate and adjust the naming choices and transitions between the surfaces, transition choices were experimentally and qualitatively established Extend the concept to different case studies to apply real data sets and real world warpage problems Already working with a microelectronics industry leader on extending these concepts, but more feedback is appreciated

43 Thank You