MOVING AUTOMOTIVE ELECTRONICS FROM … · 2017. 10. 23. · PHYSICS OF FAILURE CAE APP James...

MOVING AUTOMOTIVE ELECTRONICS FROM

RELIABILITY/DURABILITY TESTING

TO VIRTUAL VALIDATION MODELING USING A

PHYSICS OF FAILURE CAE APP

James McLeish, DfR Solutions

Russell Haeberle, Magna Electronics

2014 RAMS – Paper – McLeishPaper # SAE 2014-01-0233SAE INTERNATIONAL

Traditionally, Quality, Reliability, Durability (QRD) and Safety of

Vehicular Electrical/ Electronics (E/E) Systems Depended On Rounds of

Design-Built-Test-Fix (DBTF) Reliability & Durability Growth Testing.

• Requires 12-16 or more weeks of Accelerated Life Testing (ALT)

• Increasing Vehicle E/E content, increases burden on test labs & budgets

• Larger mass of electric/hybrid vehicle power modules slows test

acceleration that can extend life testing to 5-6 months

• Durability failures tend to occur late in life testing with the required root

cause investigation often stress budgets & schedules

• Physics of Failure (PoF) Reliability Assessment combines dynamic stress

analysis of usage and environmental conditions with failure mechanism

models to perform a durability simulation that identify failure susceptibilities

and calculate reliability behavior over time.

• Performed in a Computer Aided Engineering (CAE) App Environment

PoF based durability simulations and reliability assessments are

starting to reveres the burden of increasing vehicular E/E content.

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Abstract


Computer Aided Engineering (CAE)

CAE - computers programs used to perform engineering analysis tasks

• Expedites the application of scientific principles to determine the properties or

performance characteristics of a design, (a.k.a. CAA Computer Aided Analysis).

• Evolved to support many different engineering disciplines & industries:

• Mechanical, Civil/Structural, Electrical/Electronics, Thermal, Hydraulics . . .

• Automotive, Aerospace, Naval, Construction, Mining, Power Generation . . .

1. Stress analysis using FEA (Finite Element Analysis)

2. Computational Fluid Dynamics (CFD) for thermal & fluid flow analysis

3. Kinematics & Mechanical event simulation (MES)

5. Process simulation (casting, molding, and die press forming)

6. Product Optimization

7. Circuits & Electromagnetics Analysis

3

2014 RAMS – Paper – McLeishPaper # SAE 2014-01-0233SAE INTERNATIONAL 4

CAE Evaluations & Optimization of Design Alternatives, as the

Design is Created has Benefited Many Aspect of Vehicle Engineering

Crashworthiness &

Safety

Vehicle Dynamics

Durability

Energy

Performance Integration

Noise & VibrationAerodynamics

Thermal

Vehicle Structure

However, E/Es have traditionally gravitated to Circuit, Electromagnetic & Software

CAE Tools & have been less interested in Hardware Structural Analysis CAE


CAE Tools & Methods

Most CAE programs are model “creation” tools

• Like a blank spread sheet or word document they enable the user to

first create every element and then run an analysis.

• But this requires a long model creation effort

and requires the user to be:

• Very experienced with the

CAE modeling program.

• Highly knowledgeable in the specific

physics and engineering discipline

of the item being analyzed.

• PhD level expertise is often required.

• Availability and cost of this level of

expertise has sometimes limited the

expansion of CAE methods from

reaching many areas where they

could be beneficial.

5

A Blank Canvas


An Emerging Trend

- Application Specific CAE Apps

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• Application Specific, Customized

CAE Solutions.

• Auto guided, specific function, CAE

Apps or analysis templates are

created to provide a common,

reusable semi-automated interface

• Pre-programed, off the shelf ready,

similar to smart phone or tablet

Apps.• Regularly needed product

optimization

• Frequently encountered problems.

• Allows product teams to perform

expert level CAE analysis without a

rare, costly, CAE expert

• See Article at:” http://www.sae.org/mags/SVE/10767

http://www.sae.org/mags/SVE/10767


Physics of Failure Reliability Assessment

Combines dynamic stress analysis of usage & environmental conditions

with failure mechanism models to perform a durability simulation

• Identifies failure susceptibilities & calculates reliability behavior over time.

• Based on Research into “CAUSE & EFFECT” Relationships in Failure Mechanisms

& The variable factors that makes them “APPEAR” to be Random Events.

• Combination of Material Science, Physics & Chemistry with

Statistics, Variation Theory & Probabilistic Mechanics.

• Failure of devices or structures (i.e. hardware) are due to:

• The gradual degradation (wearout) or

• Rapid disruption (overstress) due to encounters with “Excessive Stresses” from the loads an item is exposed to

• Thermal, Electrical, Chemical, Moisture, Vibration, Shock, Mechanical Loads . . .

• Failures can also occur prematurely due to fabrication or assemble defects, excessive variable factors or even design errors that weakens the items to reduced to endurance capabilities

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Sherlock ADA - A Tool Suite of CAE Apps for

PoF Durability Simulations & Reliability Assessments

Reliability Assessments of Electronic EquipmentFast, Semi-Automated

• Enables durability simulations to be interactive with design creation

• To rapidly evaluate the Durability/Reliability impact of design choices

8

It is not at the

Iphone or Droid

App store.

But yes there

is now a

Physics of

Failure

Durability

Simulation App


4 Steps of a PoF CAE App Analysis

1) Design Capture – Circuit board CAD files provides

the inputs to the modeling software & calculation tools.

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2) Life-Cycle Definition – define the reliability/durability

objectives and expected environmental & usage conditions

(Field or Test) under which the device is required to operate.

3) Load Transformation – auto creates a Finite Element

Analysis to calculate and distribute the environmental

and operational loads across a circuit board to the

individual parts and features.

4) PoF Durability Simulation/Reliability Analysis

& Risk Assessment – Failure Mechanisms algorithms

applied to the model & stress conditions to performs a

design & application specific durability simulation to

calculates life expectations, reliability distributions &

prioritizes risks.


Step 1: Design Capture - Import PCBA Layout

(Gerber, ODB++, Eagle & Valor CAD & BOM Part Lists)

10


Step 1: Design Capture - Mech. Stack up Analysis define PCB

Laminate & Layers to Calculate Substrate

Performance

11

Calculates:

Thickness

Density

CTE x-y

CTE z

Modulus x-y

Modulus z

From the

material

properties

of each layer

Using the Built

in Laminate

Data Library


Step 1: Parts ID, Management & Linkage to

Built In PoF Component Model Library

Minimizes data entry through intelligent parsing and embedded

electronic components package and material databases

12


Step 2: Define Life Cycle - Field or Test Environment &

Usage Condition – Use Pre-Programs Standards or Define

Your Own

Define Detail Lifetime Thermal, Vibration & Shock Stress Profiles

13


Step 3: Load Transformation - Automated FEA Mesh Creation

to Calculate Stress Distribution Across the PCBA

14


Step 3) Load Transformation Automated FEA Meshing & Analysis

Determines Stress Distribution Across the PCB & to Components

Automatic Mesh Generation • Days of FEA modeling and

calculations, executed in minutes

• Without a FEA modeling expert.

15

1st Natural Frequency

Calculates PCB Stress

Distribution for use in

Fatigue/Fracture Analysis

- Harmonic Vibration

- Random Vibration

- Shock

2nd Natural Frequency


Step 4: PoF Durability Simulation & Reliability Risk

Assessments of a Safety Critical Module

- Thermal Cycling Solder Fatigue Example

N50 fatigue life calculated for each of 705 components (68 unique part types), with

risk color coding, prioritized risk listing and life distribution plots based on

known part type failure distributions (analysis performed in <30 seconds) after

model created. • Red - Significant portion of failure distribution within service life or test duration.

• Yellow - Lesser portion of failure distribution within service life or test duration.

• Green - Failure distribution well beyond service life or test duration.(Note: N50 life - # of thermal cycles where fatigue of 50% of the parts are expected to fail)

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Parts With Low Fatigue Endurance

Found In Initial Design

~84% Failure Projection

Within Service Life,

Starting at ~3.8 years.


Step 4: PoF Durability/Reliability Risk Assessment

Enables Virtual Reliability Growth

Identification of specific reliability/durability limiting or deficiencies,

of specific parts in, specific applications

• Enables the design to be revised to meet reliability/durability

objectives: WHILE STILL ON THE CAE SCREEN

Failure Risk Plot of the

same project after

fatigue susceptible

parts replaced with

electrically equivalent

parts in component

package suitable for

the application.

Life time failure risks reduced from ~84% to ~1.5%

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Step 4: PoF Durability/Reliability Capabilities

Plus Optional MIL-STD-217 Random Failure Rate Calculator

• Thermal Cycling Solder Attachment Fatigue

• Thermal Cycling PCB PTH Via Barrel Cracking Fatigue

• Vibration Solder Fatigue

• Shock Solder Fracture

• Actuarial (Constant Failure Rate/MTBF Tabulations)

• Conductive Anodic Filament Risk Assessment

• Stress load in Fracture Risk Assessments

• ICT Test Stress Analysis

• Compliant Pin Connector Insertion

• ISO-26262 Functional Safety FMECA Generator

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Step 4: PoF Durability Simulations/Failure Risk Life Curves for

each Failure Mechanism Tallied to Produce a Combined Life Curve

Detailed Design & Application Specific PoF Life Curves are Far More Useful

than a simple single point MTBF (Mean Time Between Failure) estimate.

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PTH Thermal

Cycling Fatigue

Wear Out

Thermal

Cycling

Solder

Fatigue

Wear Out

Vibration

Fatigue

Wear Out

Over All

Module

Combined

Risk

Cumulative Failures from

Generic, Actuarial, Failure Rate

Tables in MIL-HDBK-217


Step 4: PoF Durability/Reliability Risk Assessment Results

Available in 6 Different Output Formats

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Step 4: PoF Durability/Reliability Risk Assessment

- Automated Report Generation

Comprehensive reports

generated in PDF format

• Key summary points

• Detailed inputs and findings

• Result plots and tables

• User control over contents

50-100 page professionally

formatted document

produced in seconds

21


A vehicle control module was developed with 750 SMD (Surface Mount Devices).

• Initial prototype thermal solder fatigue testing was successful.

• Production level testing revealed solder fatigue cracks in three QFN-32s ICs

(Quad Flat No-lead w/32 terminals).

• No process or design changes were made between prototype & process

verification testing

• However a significant difference in solder thickness was noted.

• After several investigations thin solder was the primary suspected

root cause of the fatigue cracking.

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Case Study - Simulation Aided Testing (SAT) Using the Sherlock PoF CAE App @ Magna Electronics

Solder CrackProduction QFN w/Solder Fatigue Crack Un-failed Prototype QFN


QFN ICs are designed to have thin packages & low profile solder joints • IC Packages that make thin & light portable

consumer electronics possible • But low profile solder joints have high CTE Mismatch Expansion-Contraction

shearing angle stresses which Reduces Durability Capabilities

• The IC Industry is prioritizing development of new ICs in QFN packages• The auto industry needs to be able to able to evaluation & Validate which QFN ICs

are suitable for High Reliability & Safety Critical Vehicle Applications.

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Comparing Thermal Cycling Durability of

QFN ICs - Thermal Cycling Reliability

Laminated BGAs:

TTCL: 3,000 to 8,000FNL CSP:

TTCL: 1,000 to 3,000*TTCL = Typical Thermal Cycle Life

During -40° to +125°C TestingPackage TypeTypical Thermal Cycles to Failure

(-40C to 125C)

QFP >10,000

BGA 3,000 – 8,000

QFN 1,000-3,000

Gull Wing Leaded QFPs

TTCL: >10,000


Prototype PCBs (Printed Circuit Boards)

samples were not manufactured correctly.

• Solder mask plug protruded from the

thermal via onto the soldering surface

under the QFN, creating a standoff

• The standoff prevented extrusion of

solder from under the QFN resulting in

thicker solder under the QFN I/O pins

Production level PCB had no protrusions

of solder mask onto solder surface

resulting in thinner solder under the QFN

• Thicker solder acts like a flexing spring to absorb differences in

Thermal Cycling Expansion/Contraction between the PCB and QFN IC

• Thin QFN Solder results in a large CTE Shear Stress Angle, which Accelerated Solder Fatigue

• Thicker QFN Solder results in a smaller CTE Shear Stress Angle, which Reduces Solder Fatigue Rates

Alternative means to achieve thicker solder under the QFNs

in productions were developed to resolve to problem

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What Caused Solder Thickness Variation?

QFN Heat Slug

PCB Pad

Solder Mask

Solder

Thermal

Via

Solder Mask

Protrusion

2014 RAMS – Paper – McLeishPaper # SAE 2014-01-0233SAE INTERNATIONAL 25

Sherlock Analysis Modeling Different Solder Thickness

The Sherlock solder fatigue durability simulation illustrated the effect of solder thickness

on QFN IC fatigue life identifies: “Time to 1st Failure” & the “Failure Growth Rate”

@ 35 mm solder thickness - mean solder

fatigue life is a RED Risks at 11.5 Yrs.

@ 50 mm solder thickness - mean solder

fatigue life is GREEN Good at 21.9 Yrs.

43% Thicker 50 mm Solder

Improves Durability/Reliability• Exceeds Reliability Goal

• 0.5% Durability Extended to 15.6 Yrs.

• 11 Yr. Failure Risk

Reduced to 0.18%

Thin 35 mm Solder Thickness Misses

Programs Reliability Durability Goal • Durability Simulation Indicates that the

<0.5% Accumulated Failure Risks @ 11Yrs.

would NOT be met

• 0.5% Exceeded at 8.7 Yrs.


With a few days & rounds of QFN issue PoF durability simulations

• Life Plot Results Correlated Well with the Physical Durability Tests

• Provided insight that correctly identified and quantified the

root cause of the premature solder fatigue

• Obtaining the same results by tradition physical testing methods would

of required months of costly sample preparation and physical testing.

• The QFN incident demonstrated the value of Physics of Failure Modeling

In the development of Vehicular Electronics and was used in

validating the Sherlock CAP App at Magna Electronics

• It is now being increasing used at Magna Electronics and integrated into the

product development schedule to provide early evaluation of the durability and

reliability capabilities of new automotive electronic modules and components

while the design is still on the CAE screen.

• Allows reliability concerns to be identified and resolved

without the time and expense of tradition

physical D-B-T-F reliability growth testing

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QFN Case Study Aftermath


In Conclusion: the Sherlock ADA CAE App is a

New, Revolutionary, Awarding Winning Tool Suite For Virtual Durability/Reliability Risk Assessments of

Electronic Equipment

27

March 2014

New March 2014

“Design for Reliability

with Computer Modeling”Read Full Article @

http://pcdandf.com/cms/co

mponent/content/article/17

1-current-issue/10722-

design-validation

http://pcdandf.com/cms/component/content/article/171-current-issue/10722-design-validation


Want to Know More – Suggested Reading

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Questions

Thank you for your attention.

Any questions?

For More Information or Copies of the

Presentation Slides Contact:

[email protected]

[email protected]

301-474-0607

or Down load from:

http://www.dfrsolutions.com/resource-center/our-publications/

29

mailto:[email protected]

mailto:[email protected]

http://www.dfrsolutions.com/resource-center/our-publications/

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