Background A leading U.S. automotive manufacturer initiated an update to their product qualification process to help accelerate development and deliver new products to market sooner. To accomplish this goal, the duration of the accelerated life test was reduced by increasing the severity and decreasing the duration of the temperature cycle. During an initial trial of this updated qualification test on an electronic module, several components experienced failure. A failure analysis identified the failure mode as solder joint fatigue. Contrary to the original intent, these unexpected failures introduced significant delay as the two parties, customer and supplier, worked to determine the root-cause of these failures and their relevance to actual field environments. Solution To help accelerate this process, and provide quantitative findings, an analysis of the module design using Sherlock was performed. Sherlock Automated Design Analysis software uses a Physics of Failure analysis to allow design and reliability engineers to predict and prevent product failure earlier in the design process saving time, money, and improving product performance. Results Sherlock’s initial evaluation of the module design correctly predicted which parts would fail, confirming the field results of the accelerated life test conducted by the manufacturer. Results from Sherlock also helped both parties understand how the test environment related to ten (10) years of a realistic worst-case use environment. This information, provided by the Sherlock analysis in less than one day, allowed critical, time-sensitive product development to continue as originally planned. The automotive manufacturer is now using Sherlock Automated Design Analysis to evaluate additional electronic module redesigns. The use of Sherlock will provide the manufacturer with rapid feedback on product design and enable them to deliver more reliable products to market in less time.

1. ENHANCING & PREDICTING RELIABILITY
OF AUTOMOTIVE ELECTRONICS USING
PHYSICS OF FAILURE MODELING
Presented by:
Cheryl Tulkoff
DfR Solutions
ctulkoff@dfrsolutions.com

2. Electronics are integrated in every aspect
of the modern auto
2

3. Motivation for Physics of Failure (PoF)
Modeling
• Ensuring sufficient vehicle reliability is critical
• Markets lost and gained
• Reputations persist for years or decades
• Hundreds of millions of dollars at stake
• Opportunities for improvement in automotive:
• Warranty costs range from $75 to $700 per car
• Failure rates for electronic systems in vehicles range from 1 to
5% in first year of operation
• Hansen Report (April 2005)
• Traditional reliability prediction methodologies don’t
work!

4. Reality of Design for Reliability (DfR)
• Ensuring reliability of electronic
designs is becoming increasingly
difficult
• Increasing complexity of electronic
circuits
• Increasing power requirements
• Introduction of new component and
material technologies
• Introduction of less robust
components
• Results in multiple potential
drivers for failure
4

5. Reliability Assurance -- Definition
• Reliability is the measure of a product’s ability to
• …perform the specified function
• …at the customer
• …over the desired lifetime
• Assurance is “freedom from doubt”
• Confidence in your product’s capabilities
• Typical approaches to reliability assurance
• ‘Gut feel’
• Empirical predictions (MIL-HDBK-217, TR-332)
• Industry specifications
• “Test-in” reliability
• Sherlock is a reliability assurance software based upon physics
of failure algorithms
5

6. Perspective on Desired Product Lifetimes
• Low-End Consumer Products (Toys, etc.)
• Do they ever work?
• Cell Phones: 18 to 36 months
• Laptop Computers: 24 to 36 months
• Desktop Computers: 24 to 60 months
• Medical (External): 5 to 10 years
• Medical (Internal): 7 years
• High-End Servers: 7 to 10 years
• Industrial Controls: 7 to 15 years
• Appliances: 7 to 15 years
• Automotive: 10 to 15 years (warranty)
• Avionics (Civil): 10 to 20 years
• Avionics (Military): 10 to 30 years
• Telecommunications: 10 to 30 years
6

7. Limitations of Current DfR
• Too broad in focus - not electronics focused
• Too much emphasis on techniques and not answers
• Failure Mode & Effects Analysis (FMEA) and Fault Tree Analysis
(FTA)
• FMEA/FTA rarely identify DfR issues because of limited focus on the
failure mechanism
• Overreliance on MTBF calculations and standardized
product testing
• Incorporation of Highly Accelerated Life Testing (HALT)
and failure analysis is too little, too late
• Frustration with ‘test-in reliability’ – no such thing!
7

8. DfR and Physics of Failure (PoF)
• Due to some limitations of classic DfR, there has been an
increasing interest in PoF
• Also known as Reliability Physics
• PoF Definition: The use of science (physics, chemistry,
etc.) to capture an understanding of failure mechanisms
and evaluate useful life under actual operating conditions
8

9. • Failure of a physical device or structure can be attributed to
the gradual or rapid degradation of the material(s) in the
device in response to the stress or combination of stresses
such as:
• Thermal, Electrical, Chemical, Moisture, Vibration, Shock,
Mechanical Loads . . .
• Failures May Occur:
• Prematurely
• Device is weakened by a variable fabrication or assembly defect
• Gradually
• wear out issue
• Erratically
• Encounters an excessive stress that exceeds the
capabilities/strength of a device
Physics of Failure Definitions

10. Why PoF is Now Important
FailureRate
Time
Electronics: 1960s, 1970s, 1980s
No wearout!
Electronics: Today and the Future
Wearout!
10

11. PoF and Wearout
• What is susceptible to wearout in electronic designs?
• Ceramic Capacitors (oxygen vacancy migration)
• Memory Devices (limited write cycles, read times)
• Electrolytic Capacitors (electrolyte evaporation, dielectric dissolution)
• Resistors (if improperly derated)
• Silver-Based Platings (if exposed to corrosive environments)
• Relays and other Electromechanical Components
• Light Emitting Diodes (LEDs) and Laser Diodes
• Connectors (if improperly specified and designed)
• Tin Whiskers
• Integrated Circuits (EM, TDDB, HCI, NBTI)
• Interconnects (Creep, Fatigue)
• Plated through holes
• Solder joints
11

12. Automotive Electronics Challenge
Enduring > 150,000 Miles of Usage & 10 Years in Harsh Environments
12
20-30 30-40 40-50 50-40 60-70 70-80 80-90 90-
100
100-
110
110-
120
120-
130
130-
140
140-
150
150-
160
160-
170
170-
180
180-
190
190-
200
210-
220
220-
230
Temperature bands (Deg. F)
Time(Hrs)
Time at Temperature
87,600 Hrs over 10 years
Seasonal Varying Thermal Cycles
Over Diverse Regional Climates
Vibration
Interior: 10-1000hz 3-4 Grms
On Engine: 10-2000Hz 18-20 Grms
Shock
Road Events: up to 20 Gs
Collisions: up to 100 Gs
Humidity – Water Splash
Temperature Range:
Interior: -40 to +85C
Under hood: -40 to +125C
Electromagnetic
Noise

13. The Traditional Product Development Process Approach:
A Series of Design - Build - Test - Fix Growth Events
Emphasis
Sketchy/
Loosely
Defined
Req’mts
Design
then
Build
Product
QRD+P
Growth by
Rounds of
Test Dev/Val
Process
Costly
Redesign
/Retool
Fixes
Start
Production
Watch &
Study
Warranty
Emphasis Emphasis
Essentially Formalized Trial & Error
Part 1:
Formal Lab & Track Dev/Val Trial
& Error Approach to
Finding & Fixing Problems.
Part 2:
Customers Become the Unwitting
Test Subjects in Continued Trial
& Error Tests in the Real World
13

14. Traditional Reliability Growth in Product
Development
Today, This Is Not Enough!
DESIGN - BUILD - TEST - FIX
(D-B-T-F)
6) REPEAT 3-5
Until Nothing Else
Breaks Or You Run
Out Of
Time/Money.
Yes
No
4)
Faults
Detected
?
5) Fix Whatever
Breaks.
2) Build 3) Test1) Design
14

15. Vehicle Electronics Reliability Prediction Case Study (1990s)
- Actuarial Predictions Compared to Actual Field Failure Rate
Note:
P.C. = Passenger Compartment
U.H. = Under hood, the Hotter
Engine Compartment

16. 0
10
20
30
40
50
60
70
80
90
0 6 12 18 24 30 36 42 48 54 60
DPTV
Months After Sale
1st MY
2nd MY
3rd MY
4th MY
5th MY
6th MY
Reliability Growth Extends into Production
• Results in high Warranty Cost & Customer Dissatisfaction
16
MY =
Model
Year
DPTV =
Defects
per 1000
vehicles

17. If Parts Pass Qual Testing, Why Do Field failures Still Occur?
10%
5%
2%
1%
0.5%
0.2%
0.1%
0.05%
Probability of Detecting a Problems of Size “X” with “N” Parts on Test
17

18. Noise & Vibration
Safety
Vehicle Dynamics
Durability
Therm
al
The Auto Industry Has Reaped Many
Benefits from Virtual, CAE Tools
Vehicle Structure Energy
Aerodynamics
Performance Integration
A Result of
Initiatives to:
Migrate
Evaluations
from Road
to Lab to
Computer,
at the
Vehicle,
Subsystem &
Component
Level

19. • Complexity and vehicle electrification
prompting a major change in design processes.
• Intense competitive pressure to improve
efficiency & effectiveness
• Combination of physical and virtual testing
accelerates the product development process
by early identification of deficiencies & what ifs
• Physics based models make it easier to try out
new designs
• Simulations can be created and run in far less
time & cost than building and testing physical
prototype
Automotive & Computer Aided Engineering (CAE)
19

20. By 2004 GM was able to reduce vehicle road testing to the point that the southern portion of their
Mesa Az. Proving Grounds was sold.
GM now operates with a much smaller DPG in Yuma Az. and realized a significant reduction in
structural costs.
Test Model
As the use of modeling increases,
dependence on physical testing
can be reduced and refocused.
Reduce Dependence on Costly Design, Build,
Test, Fix (DBTF) Method
20

21. SherlockADA–A
ReliabilityAssurance CAE Tool Suite
- the Physics of FailureApp.
It is not at the
Iphone or Droid
App store.
But yes there
is now a
Physics of
Failure
Durability
Simulation App
21

22. The 4 Parts of a Sherlock PoF Analysis
1) Design Capture - provide industry standard inputs
to the modeling software and calculation tools
2) Life-Cycle Characterization - define the reliability/durability
objectives and expected environmental & usage conditions
(Field or Test) under which the device is required to operate
3) Load Transformation – automated calculations that
translates and distributes the environmental and
operational loads across a circuit board to the
individual parts
4) PoF Durability Simulation/Reliability Analysis
& Risk Assessment – Performs a design and application
specific durability simulation to calculates life
expectations, reliability distributions & prioritizes risks
by applying PoF algorithms to the PCBA model
22

23. MIL-HDBK-217
• Detailed Design and Application Specific PoF Life Curves are Far More Useful that a
simple single point Constant Failure Rate (i.e. MTBF) estimate.
PoF Simulations Reliability Life Curves for Each Failure Mechanism
Produce a Life Curve for the Entire Module
PTH Thermal
Cycling Fatigue
Wear Out
Thermal
Cycling
Solder
Fatigue
Wear Out
Vibration
Fatigue
Wear Out
Over All
Module
Combined
Risk
CumulativeProbabilityofFailure(%)
Cumulated Failures from Constant
Failure Rate Tables in MIL-HDBK-217
23

24. Sherlock Automotive Modeling Process
• Steps involved in running a modeling analysis:
• Design Capture
• Define Reliability Goals
• Define Environments
• Add Circuit Cards
• Generate Inputs
• Perform Analysis
• Interpret Results
24

25. Design Capture
• Imports standard PCB CAD/CAM design files (Gerber / ODB++)
to automatically create a CAE virtual circuit board model

26. Design Capture - Define PCB Laminate & Layers
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

27. Design Capture - Import BOM Parts List
• Recognizes Supplier
Part Numbers and
Standard
Industry/JEDEC
package type names
• Correlate parts to the
PCBA layout &
Sherlock’s libraries of
component geometry
size and material
property to the part’s
PCB locations.
• Info Source Identified
by Color Coding.
• Missing Data, Data
Errors or Correlation
Concerns are Flagged.

28. Design Capture - Automated FEA Mesh
Generation
28

29. Define Reliability Goals
• Identify and document two key metrics
• Desired lifetime
• Defined as time the customer is satisfied with
• Should be actively used in development of
part and product qualification
• Product performance
• Returns during the warranty period
• Survivability over lifetime at a set confidence
level
• MTBF or MTTF (try to avoid unless required
by customer)
29

30. Define Field Environment
• Approach 1: Use industry specifications like SAE J1211
• Advantages
• No additional cost!
• Agreement throughout the industry
• Disadvantages
• Always worse or easier than actual (by how much, unknown)
30

31. Define Field Environment (cont.)
• Approach 2: Based on actual
measurements of similar products in similar
environments
• Determine average and realistic worst-case
• Identify all failure-inducing loads
• Include all environments
• Manufacturing
• Transportation
• Storage
• Field
31

32. Environment Profiles in Sherlock
• Define Thermal, Vibration & Shock Stress Profiles

33. Auto Electronics Field Environment Example
• Outside the engine compartment with minimal power dissipation,
diurnal (daily) temperature cycle provides the primary degradation-
inducing load
• Absolute worst-case: Max. 58ºC, Min. -70ºC
• Realistic worst-case: Phoenix, AZ (USA), shown below
• Add +10ºC due to direct exposure to the sun
Month Cycles/Year Ramp Dwell Max. Temp (
o
C) Min. Temp. (
o
C)
Jan.+Feb.+Dec. 90 6 hrs 6 hrs 20 5
March+November 60 6 hrs 6 hrs 25 10
April+October 60 6 hrs 6 hrs 30 15
May+September 60 6 hrs 6 hrs 35 20
June+July+August 90 6 hrs 6 hrs 40 25
33

34. Environmental Profiles
20-40
40-60
60-80
80-
100
100-
120
120-
140
140-
160
160-
180
60-80
80-100
100-
120
120-
140
140-
160
160-
180
180-
200
200-
220
Valley Temp. Band
(Deg F)
Peak Temp. Band
(Deg F)
20-30 30-40 40-50 50-40 60-70 70-80 80-90 90-
100
100-
110
110-
120
120-
130
130-
140
140-
150
150-
160
160-
170
170-
180
180-
190
190-
200
210-
220
220-
230
Temperature bands (Deg. F)
Time(Hrs)
Time At Temperature
Hours Over 10 Years at Phoenix Az.
Number of Thermal Cycles
Over 10 Years At Phoenix Az.
Temperatures as measured at Proving Grounds at the
front face of an vehicle instrument panel in a black car
left out in an open parking lot under the full Arizona sun
with the windows rolled up

35. Life-Cycle Characterization - Mech. Vibration & Shock
• Define Dynamic FEA Load
• Random Vibration, Harmonic Vibration, Shock
• Pre-Populated easy to use Drop-Down Menu & Pop up Windows
• Easy to use, Customizable

36. Software Modeling Capabilities
• Analyses currently available:
• CAF – Conductive Anodic Filament
Formation
• MTBF via MIL-HNDBK-217
• Plated Through Hole Fatigue
• Solder Joint Fatigue
• Vibration
• Shock
36

37. Conductive Anodic Filament Analysis
• Conductive anodic filament (CAF) formation occurs due to
electrochemical migration of copper between two adjacent vias
• Within the PCB laminate and not on the surface
• Primary factor driving CAF is damage to the laminate during via
drilling
• Software evaluates edge-to-edge spacing of all the vias on the
board
• Estimates the risk of CAF formation based on the damage zone
around each via
• Considers as how well the product was qualified with CAF testing.
37

38. • The majority of electronic failures are thermo-
mechanically related*
• Thermally induced stresses and strains
• Root cause: excessive differences in coefficient of
thermal expansion
*Wunderle, B. and B. Michel,
“Progress in Reliability Research in
Micro and Nano Region”,
Microelectronics and Reliability,
V46, Issue 9-11, 2006.
A. MacDiarmid, “Thermal Cycling Failures”, RIAC
Journal, Jan., 2011.
Thermal Fatigue
38

39. The Typical Weak Links
• Plated Through Holes
• Usually high aspect ratio plated
though holes
• Rarely microvias unless a
manufacturing defect is present
• Solder Joints
• 2nd Level interconnects
• Joints used to connect the
component to the circuit board
• 1st Level interconnect
• Joints used to connect the die to
the package
39

40. Plated Through-Hole (PTH) Fatigue
• PTH fatigue is the
circumferential cracking of
the copper plating that
forms the PTH wall
• Driven by differential
expansion between the
copper plating (~17 ppm)
and the out-of-plane CTE of
the printed board (~70 ppm)
• Validated industry failure
model available
• IPC-TR-579
40

41. Solder Joint Fatigue
• Two most common solder types are available for modeling.
• Eutectic tin-lead (SnPb)
• Lead-free SAC 305 (Sn-3.0%Ag-0.5%Cu)
• Specified at the board or component level
• Solder Fatigue Model : Modified Engelmaier
• Semi-empirical analytical approach
• Energy based fatigue
41

42. 42
Vibration Fatigue
 Lifetime under mechanical cycling
is divided into two parts
 Low cycle fatigue (LCF)
 High cycle fatigue (HCF)
 LCF is driven by plastic strain
(Coffin-Manson)
 HCF is driven by elastic strain
(Basquin)
 b
f
f
e N
E
2

 
 c
ffp N2 
-0.5 < c < -0.7; 1.4 < -1/c > 2
-0.05 < b < -0.12; 8 > -1/b > 20
42

43. Vibration Software Implementation
• The software uses the finite element results for board
level strain in a modified Steinberg-like formula that
substitutes the board level strain for deflection and
computes cycles to failure
• Critical strain for the component
Lc
c

 
ζ is analogous to 0.00022B but modified for strain
c is a component packaging constant, 1 to 2.25
L is component length
43

44. Shock
• Implements shock based upon a critical board level strain
• Will not predict how many drops to failure
• Either the design is robust with regards to the expected shock
environment or it is not
• Additional work being initiated to investigate corner
staking patterns and material influences
44

45. PoF Reliability Auto Case Study
Thermal Cycling Solder Fatigue
• 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)
Parts With Low Fatigue Endurance
Found In Initial Design
~84% Failure Projection
Within Service Life,
Starting at ~3.8 years.
45

46. 46
PoF Reliability
RiskAssessment Enables Virtual ReliabilityGrowth
• Identification of specific reliability/durability limits or deficiencies,
of specific parts in, specific applications, enables the design to be revised
with more suitable/robust parts that will meet reliability objectives.
• Reliability plot of the
same project after
fatigue susceptible
parts replaced with
electrically equivalent
parts in component
package more suitable for
the application.
• Life time failure risks reduced from ~84% to ~1.5%

47. Conductive Anodic Filament (CAF) Analysis
• PCB Drill Data used to analyze relationships between adjacent
PTH combinations are calculated
• Qualification process is considered
• Damage zone and laminate weave taken into consideration
• PTH risk displayed by Red, Yellow, Green color codes.

48. All IPC 4101 Laminates are not equal
ISOLA410 ISOLAIS415 Nelco N4000-29 ISOLA370HR

49. Reliability Durability Differences of 4 IPC-4101
PCB Materials under Thermal Cycling
49

50. • Automotive customer
evaluated replacement parts
• PoF modeling identified risk of replacement before
prototype. Modified design accordingly
Automotive Design Change
50

51. Fundamental Freq. 708 Hz
2) VIBRATION MODAL SIMULATIONS
Case Study - Body Control Module
1st Harmonic 1327 Hz
2nd Harmonic 1440 Hz
1) CREATE MODEL
3) DETERMINE LOCALIZED STRESS
FROM AMPLITUDE OF FLEXURE
DISPLACEMENT
Peak
.296 mils

52. Case Study - Body Control Module
5) ENHANCE FATIGUE RELIABILITY - BY OPTIMIZING
DESIGN OF CIRCUIT BOARD SUPPORTS IN HOUSING.
Cost Reduced - $.80/unit,
Mass Reduced - 19%
4) RELIABILITY SIMULATION - IDENTIFIES
SITES OF MECH. FATIGUE FAILURES & TIME TO
FATIGUE
After
Analysis
Fatigue
Life
Extended
to
1.04-1.72
Billion
Vib.
Cycles

53. Summary - Reliability Science for the Next Generation
• PoF Modeling Software
• Reduces the complexity and need for an expert
in creating and running models
• Makes PoF Analysis faster and cheaper than
traditional Design, Build, Test & Fix Reliability
Growth Tests
• Determines if a design is theoretically capable of
surviving intended environment and use
conditions.
• Validated with real testing
• Compatible with the way modern products are
designed and engineered (i.e CAD/CAE/CAM
packages).

54. Presenter Biography
 Cheryl Tulkoff has over 22 years of experience in electronics manufacturing with an
emphasis on failure analysis and reliability. She has worked throughout the electronics
manufacturing life cycle beginning with semiconductor fabrication processes, into
printed circuit board fabrication and assembly, through functional and reliability testing,
and culminating in the analysis and evaluation of field returns. She has also managed
no clean and RoHS-compliant conversion programs and has developed and managed
comprehensive reliability programs.
 Cheryl earned her Bachelor of Mechanical Engineering degree from Georgia Tech. She
is a published author, experienced public speaker and trainer and a Senior member of
both ASQ and IEEE. She has held leadership positions in the IEEE Central Texas
Chapter, IEEE WIE (Women In Engineering), and IEEE ASTR (Accelerated Stress
Testing and Reliability) sections. She chaired the annual IEEE ASTR workshop for four
years, is an ASQ Certified Reliability Engineer, and a member of SMTA and iMAPS.
 She has a strong passion for pre-college STEM (Science, Technology, Engineering,
and Math) outreach and volunteers with several organizations that specialize in
encouraging pre-college students to pursue careers in these fields.

55. Co-Author, James McLeish, CRE
 >35 years of Vehicular, Military and Industrial Product Engineering Experience
 Practical, Hands on Practicing Engineer for Design & Launch of High QRD Products
 Product Design, Development, Systems Engineering & Production (Chrysler & GM - 14 yrs)
 ESA/EFC Digital Task Force (1st Microprocessor Based Engine Controller) - Chrysler Corp.
 3 Patents Automotive Electronic Control Systems - GM Adv. Product Engineer & GM E/E Engineering Center
 System Engineering and Architecture Planning - GM Saturn Project
 E/E Engineering Manager - GM Military Vehicle
 Validation, Reliability, QA Warranty Problem Solving & Test Tech Development (GM - 16 yrs)
 E/E Reliability Manager & Technical Specialists
 Manager GM Reliability Physics (Advance QRD, Test Technology Development)
 Author or Co-author of 3 GM E/E System Reliability/Validation Standards
 Michigan Office Manager & Senior Technical Staff (DfR Solutions – 7 yrs).
 Principle Investigator for E/E Warranty/Failure Analysis and Root Cause Problem Solving
 E/E Manufacturing Process Optimization, Yield Improvement, Product Validation and Accelerated Testing
 Design Reviews for Proactive Problem Prevention
 Core Member SAE - Reliability Standards Workgroup
 DfR Solutions is an Laboratory Services, Engineering Consulting & CAE software
firm.
 Specializing in the Physics of Failure (PoF) approach to investigating & learning from all types of failures in
Electrical/Electronic (E/E) technologies with a focus on failure prevention.
 DfR provides forensic engineering knowledge and science based solutions that maximize product integrity and accelerates
product development activities, (a.k.a. the Reliability Physics approach to Total Product Integrity
 (i.e. E/E Quality, Reliability and Durability (QRD))

56. THANK YOU!
Cheryl Tulkoff
DfR Solutions
ctulkoff@dfrsolutions.com
56