ENHANCING & PREDICTING RELIABILITY

OF AUTOMOTIVE ELECTRONICS USING

PHYSICS OF FAILURE MODELING

Presented by:

Cheryl Tulkoff

DfR Solutions

ctulkoff@dfrsolutions.com

Electronics are integrated in every aspect

of the modern auto

2

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!

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

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

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

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

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

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• 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

Why PoF is Now Important Fa

ilu

re R

ate

Time

Electronics: 1960s, 1970s, 1980s

No wearout!

Electronics: Today and the Future

Wearout!

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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

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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-

230Temperature bands (Deg. F)

Tim

e (

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

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

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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) Test 1) Design

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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

0

10

20

30

40

50

60

70

80

90

0 6 12 18 24 30 36 42 48 54 60

DP

TV

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

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MY = Model Year DPTV = Defects per 1000 vehicles

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

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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

• 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

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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

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Sherlock ADA – A

Reliability Assurance CAE Tool Suite

- the Physics of Failure App.

It is not at the Iphone or Droid

App store. But yes there

is now a Physics of

Failure Durability

Simulation App

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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

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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

Cu

mu

lati

ve

Pro

ba

bil

ity

of

Fa

ilu

re (

%)

Cumulated Failures from Constant Failure Rate Tables in MIL-HDBK-217

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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

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Design Capture

• Imports standard PCB CAD/CAM design files (Gerber / ODB++)

to automatically create a CAE virtual circuit board model

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

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.

Design Capture - Automated FEA Mesh

Generation

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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)

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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)

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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

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Environment Profiles in Sherlock

• Define Thermal, Vibration & Shock Stress Profiles

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 (oC) Min. Temp. (

oC)

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

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Environmental Profiles

20-4040-60

60-8080-

100100-

120120-

140140-

160160-

180

60-8080-100

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-

230Temperature bands (Deg. F)

Tim

e (

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

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

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

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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.

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• 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

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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 39

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

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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

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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 NE

2

c

ffp N2 -0.5 < c < -0.7; 1.4 < -1/c > 2

-0.05 < b < -0.12; 8 > -1/b > 20

42

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

Lcc

ζ is analogous to 0.00022B but modified for strain c is a component packaging constant, 1 to 2.25 L is component length

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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

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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.

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PoF Reliability Risk Assessment Enables Virtual Reliability Growth

• 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%

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.

All IPC 4101 Laminates are not equal ISOLA 410 ISOLA IS415 Nelco N4000-29 ISOLA 370HR

Reliability Durability Differences of 4 IPC-4101

PCB Materials under Thermal Cycling

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• Automotive customer

evaluated replacement parts

• PoF modeling identified risk of replacement before

prototype. Modified design accordingly

Automotive Design Change

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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

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

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).

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.

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))

THANK YOU!

Cheryl Tulkoff

DfR Solutions

ctulkoff@dfrsolutions.com

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