Michael BenedekRF Components Reliability Lead

3-10-2009

Microwave DeviceReliability Characterization-The Mechanics of Life Test

Execution and Analysis

Copyright © 2009 Raytheon Company. All rights reserved.Customer Success Is Our Mission is a registered trademark of Raytheon Company.

Microwave Device Reliability Characterization-The Mechanics of Life Test Execution and AnalysisCo-Authors: Nicholas Brunelle*, Anna Hooven, Bradley Mikesell and Philip Phalon* Jr, Kurt Smith**

* Raytheon RF Components Reliability Team** Raytheon RF Components IR&D Team

Copyright © 2009 Raytheon Company. All rights reserved.Customer Success Is Our Mission is a registered trademark of Raytheon Company.

03/10/2009 Page 3

Perform All Due Diligence Testing to Establish and Maintain the MMIC Fab Process Reliability to ensure ‘NoDoubt’ Mission Assurance

Provide Reliability Expertise Within RFC, IDS and Company Wide

Anticipate Test Capability and Capacity Needs to Enable Nimble Response to Programs’ Needs

Search for New Paradigms in Testing and Reliability Benchmarks Industry Wide

Implement Lean Methods and Automation to Optimize Quantity and Enhance the Quality of Test Execution and Data Analysis

Reliability Lab Charter

03/10/2009 Page 4

Reliability Lab Test Capabilities

Life Testing: Process Reliability Monitoring DC Biased Temperature Accelerated Life Test RF Operational Life Test (S & X-Band) RF Temperature Accelerated Life Test (X-Band) Pulsed DC Electromigration (DC TALT) Current Density Testing (DC TALT)

Characterization: Capacitor Time Dependent Dielectric

Breakdown Testing LabVIEW Based Parametric Characterization Resistor TCR Characterization Light Emission Microscopy Liquid Crystal Failure Analysis

03/10/2009 Page 5

What Affects Reliability? Technical or lay, we all know that the reliability or

longevity of “things” is driven by stress

The list of life reducing stresses include: temperature, temperature cycling, humidity, voltage/electric field, current density, mechanical stress, thermo-mechanical stress cycling, radiation etc

The dominating stresses depend on the application environment.

Most of us would instinctively recognize Temperature as a common stress for many “things”.

Temperature is a common stress driver of reliability

03/10/2009 Page 6

The Focus of Today’s Presentation

Our “things” of interest are microwave devices made of compound semiconductor materials (GaAs, GaN etc)

Temperature and voltage/electric field are the important stresses in the application of microwave devices

In the space/defense environment many of the others are mitigated by the application environment.

This presentation will focus on temperature activated degradation. The reliability metrics from the statistical formalism will be introduced and the procedures to obtain them will be detailed

Main Theme: Thermally activated reliability metrics

03/10/2009 Page 7

Elements of the Statistical Formalism

The Lognormal Lifetime Distribution– Failures are distributed ‘normally’ when plotted on log time scale

The Cumulative Failure Fraction Plot– A linear plot can be taken as evidence for lognormal lifetime distribution

The Arrhenius Reaction Rate Model - t=to*eEa/kT

– The Arrhenius acceleration relationship is then

– ML1/ML2 = eEa/kT1/eEa/kT2

The Reliability Metrics from above are:– Median Life (ML) or MMTF– Sigma (σ) the dispersion – standard deviation of the log of lifetimes– Activation Energy

The Metrics: Median Life, Sigma and Activation Energy

03/10/2009 Page 8

The Lognormal Failures Distribution

Distribution is ‘normal’ when plotted on log time scale

Lognormal Failure Distribution

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1.E+2 1.E+3 1.E+4 1.E+5 1.E+6 1.E+7 1.E+8 1.E+9

Time [Hr]

Failu

re D

istri

butio

n [a

rbitr

ary]

0

20

40

60

80

100

120

Cum

ulat

ive

Failu

res

[%]

MedianLife

σ=1

15 yrMission

03/10/2009 Page 9

Trade Off Between ML and σ

To maintain ‘Same’ Reliability at lower ML, σ has to be smaller

Lognormal Failure Distribution

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1.E+2 1.E+3 1.E+4 1.E+5 1.E+6 1.E+7 1.E+8 1.E+9

Time [Hr]

Failu

re D

istr

ibut

ion

[arb

itrar

y]

1.E-02

1.E-01

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

Failu

re R

ate

[FIT

]

σ=0.5σ=1

Failure Rate in FITs through mission time is negligible

FIT is a failure unitAnd it is equivalent with 1 failure/109 hr

03/10/2009 Page 10

The Lognormal Failures Distribution

Note Margin Between Distribution Tail and Mission Time

Lognormal Failure Distribution

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1.E+2 1.E+3 1.E+4 1.E+5 1.E+6 1.E+7 1.E+8 1.E+9

Time [Hr]

Failu

re D

istri

butio

n [a

rbitr

ary]

0

20

40

60

80

100

120

Cum

ulat

ive

Failu

res

[%]

15 yrMission

MedianLife

.

03/10/2009 Page 11

The Cumulative Failure Fraction Plot

A linear plot is taken as evidence for lognormal lifetime distribution

Cumulative Failure Plot

TTF = 1031e0.516z

10

100

1000

10000

100000

-3 -2 -1 0 1 2 3Z Score

Tim

e-to

-Fai

lure

[hr]

991 20 305 10 50 70 80 90 95Q(z)

Note on the X scale both the Probability and Score scales are shown

The Plot is linearLn(TTF) = σ*z + Ln(ML)

The exponential curve fit in Excel returns the formTTF = ML* eσ*z

The extraction of ML and σ is direct

03/10/2009 Page 12

The Arrhenius Reaction Rate Model

The Ability to Thermally Accelerate Aging is Key to the Process

ML=C * eEa/kT

Or1000/T= A*ln(ML)+C

The Plot is a straight line using these scales

The logarithmic curve fit in Excel returns this form and from the slope A the Activation Energy

Ea=1000k/A=0.0862/A

k is Boltzman’s constant in eV*K-1

Arrhenius Plot

y = -0.0429Ln(x) - 1.3647

1.E+

0

1.E+

1

1.E+

2

1.E+

3

1.E+

4

1.E+

5

1.E+

6

1.E+

7

1.E+

8

1.E+

9

Time [hr]

Tch

[°C

] (10

00/T

sca

le)

450400350

300

250

200

150

100

Ea [eV]

1.5

1.0

2.0

Missionconditions

Acceleratedconditions

03/10/2009 Page 13

Life Test Scope

FET Test Vehicles and -20% ΔId Failure Criterion

Life Tests at minimum 3 temperatures are required to establish a credible trend

Tch for the Life Tests is determined from self heating due to DC operating power dissipation and base plate temperature setting

Test Vehicles are 12 Schottky Gate Field Effect Transistors per temperature group

20% Decrease in Drain Current is the Failure Criterion

Drain Current is a key performance parameter and it is correlated with RF Power output capability

03/10/2009 Page 14

Life Test Data Analysis

Times to Failure are indicated by arrows on the Time Scale

Drain Current aging at Tch=329°C - Linear trend plot

Drain Current Aging Trend

-50-40-30-20-10

01020304050

0 500 1000 1500 2000Time [hr]

Del

ta Id

[%

]

1

2

3

4

5

6

7

8

9

10

11

12

Linear Plot

03/10/2009 Page 15

Life Test Data Analysis

Logarithmic trend plot is a better visual indicator of ML

Drain Current aging at Tch=329°C - Logarithmic trend plot

Drain Current Aging Trend

-50-40-30-20-10

01020304050

0.1 1 10 100 1000 10000Time [hr]

Del

ta Id

[%

]1

2

3

4

5

6

7

8

9

10

11

12

Logarithmic Plot

The Times-to-Failare tabulated andranked and usedin the next step

03/10/2009 Page 16

Life Test Data Analysis

The Id trend plot is reduced to the TTF and Z-score data array

The Time-to-Fail values are tabulated and ranked

For each failure the cumulative failed fraction, Q, is calculated using the median ranking formula: Q=(F-0.3)/(N+0.4) F is the number of failed parts; N is the number of parts in the test

Q is converted to the z score using NORMSINV function in ExcelF

cum # failuresQ [fraction]

(F-0.3)/(N+0.4)Z score TTF [hr]

sorted

1 0.05645 -1.58528 450

2 0.13710 -1.09346 570

3 0.21774 -0.77984 670

4 0.29839 -0.52904 700

5 0.37903 -0.30802 950

6 0.45968 -0.10125 1100

7 0.54032 0.101246 1174

8 0.62097 0.308024 1200

9 0.70161 0.529045 1200

10 0.78226 0.779842 1700

11 0.86290 1.093456 1900

12 0.94355 1.585278 2100

The resulting z-score and TTF data is plotted using the Cumulative Failure Fraction Plot

03/10/2009 Page 17

The Cumulative Failure Plot Provides ML and σ Directly

The exponential curve fit in Excel returns the formTTF = ML* eσ*z

The extraction of ML and σ is direct

ML=1031hrσ=0.52

The Cumulative Failure Plot: Tch=329°C

Cumulative Failure Plot

y = 1030.9e0.5156x

10

100

1000

10000

100000

-3 -2 -1 0 1 2 3Z Score

Tim

e-to

-Fai

lure

[hr]

991 20 305 10 50 70 80 90 95Q(z)

03/10/2009 Page 18

The Cumulative Failure Plot Provides ML and σ Directly

The extraction of ML and σ is direct for all 3 temperature groups

Cumulative Failure Plot

y = 364.7202e0.5676x

y = 1030.9456e0.5156xy = 4053.4e0.3487x

y = 0.1000e-0.0000x

10

100

1000

10000

100000

Q(z) [%]

Tim

e-to

-Fai

lure

[hr]

0.01 0.1 99 99.9 99.991 20 305 10 50 70 80 90 95

Failure Criterion = -20% Id

All 3 Cumulative Failure Plots

Tch[°C] ML[hr] σ345 365 0.57329 1031 0.52308 4053 0.35

Tch and ML are ready to be plotted on the Arrhenius coordinates

03/10/2009 Page 19

The Arrhenius Plot for the 3 Life Tests

The Arrhenius Plot Provides Ea Directly

Tch ML 1000/Tch[°C] [hr] [°K-1]

345 365 -1.618329 1031 -1.661308 4053 -1.721

Tch is converted to 1000/Tch in [°K-1] Note negative sign forces Temperature increase bottom to top

ML and 1000/Tch are plotted on the Arrhenius Coordinates Ea=0.0862/A Ea=2.01eV

Arrhenius Plot

y = -0.0429Ln(x) - 1.36471.

E+0

1.E+

1

1.E+

2

1.E+

3

1.E+

4

1.E+

5

1.E+

6

1.E+

7

1.E+

8

1.E+

9

Time [hr]

Tch

[°C

] (10

00/T

sca

le)

450400350

300

250

200

150

100

Ea [eV]

1.5

1.0

2.0

Y = -A*Ln(x) - C

03/10/2009 Page 20

Reliability Metrics SummaryThe Reliability Metrics based on all 3 temperature groups used in this example are

Tch[°C] ML[hr] σ Ea[eV]

345 365 0.57329 1031 0.52 2.01308 4053 0.35

The 2.01eV Arrhenius Line Projects ML= 1.3E10 at a Mission Tch=150°CThe Conservative 1.5eV Arrhenius Line Projects ML= 2.1E8 at Tch=150°C

Extrapolate Time Unknown

Ea (eV) t1 [hr] T1 [°C] t2=?? [hr] T2 [°C]

2.01 4.05E+03 308 1.313E+10 150

1.50 1.03E+03 329 2.116E+08 150

Projections are based on the Arrhenius relationshipML1/ML2 = eEa/kT1/eEa/kT2

03/10/2009 Page 21

Reliability Metrics Summary

Normalized Failure Rate Plot is Used to Validate Our Extraction and Calculation Protocols

Normalized Failure Rate Plotsafter Goldthwaite (ref. 5)

1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

1.E+10

1.E+11

1.E-

7

1.E-

6

1.E-

5

1.E-

4

1.E-

3

1.E-

2

1.E-

1

1.E+

0

1.E+

1

Time/MedianLife

Med

ianL

ife[h

r]*Fa

ilure

Rat

e [F

IT]

σ=3

σ=2

σ=1

03/10/2009 Page 22

The Equipment/Set Up

The Equipment Uses a Servo Feedback Loop Which Adjusts the Gate Voltage to Keep Constant Drain Current

03/10/2009 Page 23

The 2nd Key Stress in the application of microwave devices - Voltage/Electric field

RF Operational Life Tests Are Used to Mitigate High Field Effects Also Known as Hot Electron Effect

Stable Po during RF Life TestStable Po during RF Life Test

04R050, Pout and IddFirst 2 of the 8 devices are DSR

20

22

24

26

28

30

32

34

36

38

40

0 200 400 600 800 1000 1200

Hours

Pout

(dB

m)

Pout 1Pout 2Pout 3Pout 4Pout 5Pout 6Pout 7Pout 8Idd 1Idd 2Idd 3Idd 4Idd 5Idd 6Idd 7Idd 8

Blue Lines are Vd=5VRed Lines are Vd=6V

EquipmentFault

RF Life Test– Output Power Trend04R050, Pout and Idd

First 2 of the 8 devices are DSR

20

22

24

26

28

30

32

34

36

38

40

0 200 400 600 800 1000 1200

Hours

Pout

(dB

m)

Pout 1Pout 2Pout 3Pout 4Pout 5Pout 6Pout 7Pout 8Idd 1Idd 2Idd 3Idd 4Idd 5Idd 6Idd 7Idd 8

Blue Lines are Vd=5VRed Lines are Vd=6V

EquipmentFault

RF Life Test– Output Power TrendRF Life Test Equipment

03/10/2009 Page 24

References

1. F.H. Reynolds, “Thermally Accelerated Aging Of Semiconductor Components”, Proceedings of the IEEE, Volume 62, No2, Feb., 1974

2. D.S. Peck and C.H. Zierdt, Jr, “The Reliability of Semiconductor Devices in the Bell System”, Proceedings of the IEEE, Volume 62, No2, Feb., 1974

3. P.A. Tobias and D.C. Trindade, “Applied Reliability”, Van Nostrand Reinhold Company, Copyright 1986

4. W. B. Nelson, Accelerated Testing Statistical Models, Test Plans, and Data Analysis”, John Wiley & Sons, Inc, Copyright 1990, 2004

5. L. R. Goldthwaite, “Failure Rate Study for the Lognormal Lifetime Model”, Proceedings of the 7th Symposium on Reliability and Quality Control, 1961 p. 208-213

6. B.S. Hewitt and M. Benedek, “Decipher The Mystery of Reliability Statistics, MicroWaves, October, 1978