using reliability physics analysis to predict thermal ... dfr... · 3/26/2019 · › bga was...

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Using Reliability Physics Analysis to Predict Thermal Cycling BGA Failures

for Aircraft Engines

March 26, 2019| Donald McNally


Copyright of DfR Solutions 2019

Agenda

Sherlock

Reliability Physics

Analysis-based

tool will

accurately predict

thermal cycling

cycles to failure

for BGAs

02Designing the test vehicle to confirm reliability physics

predictions: Selecting the best solder

Challenging environment on aircraft engines01

06How the test results correlated with the Sherlock

predictions

03

Designing the best test vehicle to confirm reliability

physics predictions: Selecting the best PWB material

and Design

04Designing the best test vehicle to confirm reliability physics

predictions: Selecting the thermal cycling range

05 How Sherlock was used to develop the predictions

2



Challenging Environment on Aircraft Engines

• Electronics operating in uncontrolled environment on an aircraft engine are exposed to significant temperature swings. − Temperature swings depend on temperature at originating and

destination locations as well as flight’s altitude.

› Electronics temperatures on flights originating in a cold location could be as low as -20 or -30°F after an overnight soak.

› Electronics temperatures on flights originating in a hot location could be as warm as 110 to 115°F or warmer based on engine soakback or exposure on a hot runway.

− Temperature swings depend on flight’s altitude.

› Typical flight for a commercial airliner will ascend to 33,000 to 42,000 ft where temperature is between -40 and -70°F.

− Worst case are short flights originating in hot regions flying to 30,000 to 35,000 feet

− A commercial airliner might involve 8 to 10 flights per day.

3



Designing the test vehicle to confirm reliability physics predictions: Selecting the best solder

• For aerospace applications, accepted solder is Eutectic 63% Tin and 37% Lead) (63Sn/37Pb).

− Rationale for this is as follows:

› Eutectic solder has lowest melting point (183 °C or 361.4 °F) of all tin/lead alloys & much lower than lead free solders (SAC305 , etc.). Low melting temperatures result in less stress to Printed Circuit Board (PCB) and electronic components during soldering reducing early stress failures

› Melting point is truly a point — not range associated with other solder compositions

• Means it goes directly from a solid to a liquid state and back to a solid state during cooling process.

• Results in a less brittle solder joint.

› Reliability and long term performance is well established and has favorable history.

› Not prone to tin whiskers like many of lead free (high tin content) solders

• Woodward decided to use both Eutectic and Innolot for thermal cycling test

4



Designing the test vehicle to confirm reliability physics

predictions: Selecting the best solder

• Challenge for lead-free− Alloy is required to support following operating environments

› High temperature: up to 120C for 25,000 hours

› Thermal Shock: -40 to 150C Air to Air

› Vibration: Random axis, G-loading will be base-lined as received, and no relative change over high temperature soak condition

› SMT compatible with a max reflow temp of 260/245C per J-STD-020

› Thin Whisker performance is better than or equal to Eutectic SnPb

• Manufacturers claims for Innolot (90.95%Sn/3.8%Ag/0.7%Cu/1.4%Sb/0.15%Ni/3%Bi) − Designed for harsh environments and under hood applications

− Classified as a lead-free legislature (RoHS etc.)

− 160C operating temperature

− Survive 2000 cycles -55C to 160C

− Minimum Reflow: 230C

− 3% Bi reduces Tin Whisker risk

− Tests have shown that Innolot outperforms Eutectic and other popular lead-fee folders when cycling from -40 to 150 C

5




predictions: Selecting the best PWB material

• Begins with an understanding of CTE (Coefficient of Thermal Expansion)

− CTE describes a number or percentage relating to how much a PCB expands as it is heated or cooled

− CTE is expressed in terms of parts per million expansion (ppm) per °C

− A typical FR-4 laminate has a CTE in range14 to 17 ppm/°C.

− Reinforcement type also affects CTE (E glass, S Glass, Woven vs. random fiber, glass vs. polyaramid, etc.)

− Generally laminates with higher glass transition temperatures have lower CTEs

− Generally PWBs with lower CTEs are:

› More expensive due to higher material cost

› More difficult to process which means higher manufacturing costs

• Includes plating, desmearing, and laminating in addition to drilling and routing (cut to profile))

6




predictions: Selecting the best PWB material

• Analysis considered BT Epoxy, Polyimide, FR-4 and Rogers materials− Considerations included:

› Musts included Low CTE - </=14.5 and Flammability (UL94 “V” rating of V-0)

› Other factors included

• Low Z axis CTE

• Cost (both material costs and manufacturing costs)

• High Glass Transition Temperature Tg of at least 170 C

• Low moisture absorption

• High speed/fast clock edges

− Decision was made to use a high temp FR4 board material (glass-reinforced epoxy laminate) with a (Tg) > 170°C, a CTE (x/y) of 15/15.

› Note: Test board was double sided laminate as opposed to a multilayer or single sided construction

− To ensure CTE of PWB material used in reliability physics prediction was correct, a CTE analysis of x/y CTE was performed by an outside lab.

› CTE measurements - 12.29/16.41 for a composite board CTE of 14.5

› Composite CTE calculated with formula =(SQRT(CTEX2+CTFY2))/SQRT(2)/1000000

7




predictions: Selecting the best PWB Design

• To simplify monitoring and allow cycling to restart quickly after a failure, board design had 4 key features

− Single daisy chain through all components for resistance based continuity measurement

− Multiple sections per component to maximize data from limited number of samples.

› BGA was divided into 4 sections and with 2 chips per board, 8 data points per board were measured

− Traces for each component or component section trace brought to edge of board for resistance measurement of individual component/component section

− Bypass jumpers to allow bypassing failed circuit segments (solder joints) and returning PWB to Cycling

8

QFP64

TSSOP8

DOE2 TOP

SSOP48

08051206

SO-14

PBGA484

QFP64

BypassJumpers



Designing the best test vehicle to confirm reliability physics


9

• Component manufacturers use 0 to 100°C per IPC 9701 “Performance Test Methods and Qualification Requirements for Surface Mount Solder Attachments”

• Others such as Freescale, whose components are subjected to an even more harsh environment such as automotive underhood applications, use range of -40 to 125°C

• Decision made to use cycling range of 0 to 125°C for thermal cycling test

− Numerous sources, including Engelmaier, state that failure mechanism for solder joint fatigue changes at cold temperatures

› “… low temperature applications, TC<0°C, for which the stress relaxation and creep in the solder joint is not the dominant mechanism1 …”

1. W. Engelmaier, “Solder joints in electronics: design for reliability”, page 7.





10

• To limit scope of test, Design of Experiments approach was used

− X1, X2 and X3 are represented by component type, dwell time and cycling range.

› Since each board has all component types on it

› Both Innolot and Eutectic boards tested in same ovens, left two elements to vary,

− Dwell time and thermal cycling range





11

• To limit scope of test, a Central Composite Design (CCD) DOE − Previously established maximum cycling range

to be 0 to 125°C

− Maximum dwell time set to 60 minutes and minimum to 15

› Typical time spent at gate between flights is 60 minutes but not less than 15

− Maxima and minima were established as “+/-alpha“ or axial points of design space (those outside of cube)

− CCD requires 5 treatment levels for a complete quadratic model

› Listed here normalized to corner points: -1.68, -1, 0, +1 +1.68), points on cube, corners (-1, +1) can be run first

› Rows 3 and 4 chosen to induce failures as quickly as possible

Row # Temp Range Dwell

1 69.5 21.6

2 69.5 53.4

3 115.5 21.6

4 115.5 53.4

5 92.5 37.5

6 92.5 37.5

7 92.5 37.5

8 92.5 37.5

9 92.5 37.5

10 60.0 37.5

11 125.0 37.5

12 92.5 15.0

13 92.5 60.0




predictions: Test setup

12

• Initial setup involved placing boards in slots in a cardboard box

• Quickly realized inadequate air circulation to allow boards to reach temperature

• Revamped fixture to maximize airflow and minimize contact with other portions of environment

• To achieve desired thermal profile

− Dwell time had be extended

− Oven had to overshoot dwell temperature by several degrees to bring board to desired temperature at start of dwell period



How Sherlock was used to develop the predictions

13

• Imported board design from Gerber file

• Entered part characteristics from part prints

• Entered thermal profile

• This one screen provides access to edit parts details and performing solder fatigue analysis



How Sherlock was used to develop the predictionsKnowns

• A number of values came from part print− Design used Island BGA

− 484 balls

− Pitch was 1 mm

− Ball channel width of 5

• Took measurements to quantify as many parameters as possible− Ball height of 0.35 mm

− Ball Diameter of 0.563

− Ball package diameter and ball pad diameter were estimated

Ball Height

Ball Diameter

14



How Sherlock Was Used to Develop the Predictions

15

• Took X-rays of die

• Used that to estimate die length and die width

• Die thickness estimated as function of overall chip thickness

Die Outline




• Tests were performed to determine CTE of BGA

• CTE calculated from slope of measured strain and temperature curves

• BGA overmold determined to be 8.855

• BGA Laminate determined to be 16.41

BGA LaminateBGA Overmold

Y=8.85E-06

Y=8.86E-06Y=16.69E-06

Y=16.13E-06

16




17

• Predictions then run by right clicking on Solder fatigue task

• Select thermal profile check box

• Results available in a matter of seconds

Short cycle prediction results: 3515 Long cycle prediction results: 3105



How test results correlated with Sherlock predictions

18

• Results

− Cycling was continued until all BGAs failed

− Performed Weibull analysis to determine “characteristic” cycles to failure

3035

3648



How test results correlated with Sherlock predictions

19

• Weibull analysis of BGA failures

Long Cycle QuART PRO output:Short Cycle QuART PRO output:



20

• Sherlock reliability physics based analysis tool did accurately predict thermal cycling cycles to failure for BGAs.

• Provides confidence Sherlock can be used to predict cycles to failure for complex BGAs operating in uncontrolled environment on an aircraft engine.

How test results correlated with Sherlock predictions:Conclusion:

Predicted

3105

Actual

3035

Predicted

3515

Actual

3648



Speaker Bio

Don McNally, Sr. Staff Electrical Engineer at WoodwardEngineering management professional with significant experience leading and managing teams in complex engineering

environments. Selected skills include:

- Development of reliability predictions for a number of major aircraft engine control applications

- Champion of using reliability physics analysis tools as part of a design for reliability process

- Management of all phases of engineering/factory introduction process from ideation to support.

- Process development and facilitation employing internal and external teams at all levels in organization.

Contact

(815)[email protected] Don McNally

21

using reliability physics analysis to predict thermal ... dfr... · 3/26/2019 · › bga was...

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