I presented this invited talk for the Silicon Valley Chapter of the IEEE Reliability Society on March 25th.

1. Design for Reliability Approach in
Magnetic Storage Industry
A. Parkhomovsky, R. M. Pelstring
Reliability Engineering, Motor Design Division,
Seagate Technology

2. Outline
• Introduction
i. Early Reliability Failure Detection
ii. Design for Reliability Approach
• Reliability Risk Assessment
i. FMEA
ii. Fault Tree Analysis
• Predictive Reliability Modeling
i. Understanding of physical processes in the product
ii. Identification of critical to reliability parameters and possible failure modes
iii. Design for Reliability Modeling using DOE and first principles approach
iv. Reliability Risk Assessment using predictive models
• Customized Accelerated Stress Tests
• Summary

3. Spindle Motor Cross Section
Journal Gap
Hub
Journal Bearing
Sleeve
Shaft

4. Design for Reliability Definition
R elia b ility v s S tre s s S u rfa ce
I After Current
• •
n Stressing
it
i
a Ea
l
A kT
Characteri stic Life e
n
J
• The tool set that supports product and
process design (during the Product
Development Cycle) to ensure customer
expectations for reliability are fully met.

5. DFSS vs. DFR
DFSS DFR
Environmental &
ANOVA Usage Conditions
VOC
Regression Life Data Analysis
Flowdown
QFD
Physics of Failure
Hypothesis Testing
FMEA
Accelerated Life Testing
Control Plans
General Linear Model
MSA Reliability Growth
Sensitivity Analysis Modeling
Warranty Predictions
DOE
Tolerancing
FA recognition
DFR focuses on achieving high quality over time and across stress
levels.

6. Design for Reliability
Control
Identify and Optimize Validate
Design
• Motor
SPC
Design
S=?
Statistical
O=?
Fault Limits
E=?
Reliability Post-
Testing
FMEA Tree
Prediction • Concept Transfer
Verification
Scard
Top
S L M
Control
D
79 Analyst: Parameter
# CTQ's
3 Total
Program
Maturity Level < 2
3
User Input
Guide 3 Missing ZST
Scorecard
Missing Gage %(P/P)
Reliability 3
New CTQ Name
3
Last Updated Input Long Term Mean and Std Dev
Menu Guide
Critical to
Default Maturity Level
(for Norm al Data) OR Long Term PNC 3
(for Non-Norm al/Attribute data) 3 Default Threshold ZST
Seagate Confidential Rev 6.0
Lower Upper Standard Gage Maturity
CTQ Name Units Mean PNC PNC ZST
Deviation %(P/P) Level
Spec Limit Spec Limit
Motor Seizure
Drive Performance Failure
Measures
Drive Contamination
Verify
Reliability
System
Parameters
Margin and
(CTR) and Reliability Robustness
Supplier Models
Capability

7. Product Development and Life Cycle Process
• Physics of Failure
Design understanding and modeling
For Reliability
• FMEA, design risk analysis,
Fault Tree
• Early Reliability Tests
Reliability
• Design Limit Tests
Verification
• Field Data analysis
Product • Design, process and
and Process Analysis product analyses
• Failure Analysis
Gap Closure though interrelated concurrent activities

8. Ensuring Reliability in the Product Development
Process
Ongoing Reliability
Production
Product Tests
Development
Transition Reliability Limit Tests
Phases
Design Maturity Reliability Limit Tests
Evaluation Early Reliability Tests
Fault Tree, FMEA,
Concept Design Rules

9. Design for Reliability Approach Strategies
1. Design Out Failure Mechanisms
2. Reduce Variation in Product Strength
3. Reduce Effects of Usage/ Environment
4. Increase Design Margins
Utilization of the design, product and process
knowledge

10. Design for Reliability Implementation Benefits
• Seagate benefits:
• Significant Reduction in Cost of development.
• Increase in the number of orders for disc drives.
• Reduction in the reserve and storage needs.
• Customer integration failures reduced.
• Field failures reduced.
• Supplier benefits:
• Larger allocation of business for suppliers commodity.
• Improved designs and specifications allowing more opportunity
for optimization of the supplier’s process.
• Improved yields with more predictability.
• Less negative surprises.

11. Best Practices Define Success
• Reliability must be designed into products and
processes, using the best available science-based
methods.
• Knowing how to calculate reliability is important,
but knowing how to achieve reliability is equally if
not more important.
• Design for Reliability practices must begin early in
the design process and be well integrated into the
overall product development cycle.

12. Comparative Resource Commitment
Shorter Development Cycles Planned Resource Level
Efficient Use of Resources
Post Release
Problem Teams
Expected
Resource Level
Actual
with Design
Resource
for Reliability
Level
Few Changes
Many Changes
Time

13. Reliability Model Feedback Loop
Design opportunity
and model gap
Event Reduced fly height Event DLC contamination causes
Description Description wear / seizure
Cond PNC 1 Cond PNC 1
identified to “break”
Cum PNC 0.0001 Cum PNC 0.0001
Function AND Function AND
Event Wear occurs in CP grooves Event Contact stress exceeds DLC
Description Description strength
failure chain.
Cond PNC 0.0001 Cond PNC 0.0001
Cum PNC 0.0001 Cum PNC 0.0001
Function AND Function AND
Event Contact occurs in thrust
Description
Cond PNC 1
Cum PNC 1
Function AND
Event Restoring force does not
Description prevent contact
Cond PNC 1
Cum PNC 1
Function
Event Op Shock
Description 1000 g's
PNC 1
Function
Fault Tree Analysis Contact relief to
Design
reduce contact
Product stress. Improvement
Op-shock
FImpact contact
250 g’s 2 ms H istog ram of Force D istrib u tion
H istog ram of S tress
300
200
200
F re q u e n c y
F re q u e n c y
Mobile 100
100
Market
0
0
1.585 1.595 1.605 1.615 1.625 1.635
23.0 23.5 24.0 24.5
S tress
F orce D istrib u tion
Model Development
Requirement
and Results

14. Fault Tree Model – Shock Failure
Fault Tree general
skeletons are
developed, then they are
easily adapted to the
particulars of each
design.

15. FMEA – Test Linkage: Example
 The Design FMEA is developed based on critical failure modes from the
fault tree analysis.
Motor Design FMEA
Item Part Potential Failure Mode Effects of Failure S Potential Cause O Design Verification E RPN
Sleeve/ Thrust excessive wear on thrust High runout,
11 motor seizure 10 2 runout measurement 2 40
Cup assy surface contamination (ECM)
Min Gap model includes all
parts tolerance allow surface and diameter parameters,
components rubbing
15 Bearing assembly motor lock up, oil leakage 9 contact or not meeting 4 bearing drag test will be correlated 1 36
while spinning
print. to journal gap.
Performance testing.
change in performance, oil wear from operating
design validated through testing
18 Bearing assembly journal wear degradation, motor lock up 8 tests, gyro scopic wear, 5 2 80
and run more that 60k cycles
& oil leak from gyro test CSS
Misalignment of
In-process height measurements,
reduced fly height, stator, magnet or bias
23 EM EM bias force too high 5 2 drawings/tolerance studies, 3 30
increased wear rate ring. Incorrect
magnetization
magnetization

16. Design Limits Test Development
Reliability tests used are developed to address high risk items in the FMEA.
 Design limit variables (e.g. groove depth, coating thickness) are selected
based upon failure mode sensitivity.
 Acceleration and stress factors (e.g. temperature, load, orientation) are
selected based on design knowledge and product environment.
Motor Reliability Design Limit Test (RDLT) Plan
Test Test Groove Depth Shaft DLC
FMEA Duration Test Test Orientation
Temp. CSS Thrust Journal Thickness
0
Savvio Motor Design Variables -VSA HSA ( C ) (cycles) ( m) ( m) ( m)
Item # RPN # (month) Qty +VSA
2 15
Motor Wear Test 11,15,18,23 81
Norminal design (control ) 3 3 3 70 72K 7.5 3.0 1.0
Max thrust cup to shaft runout + max thrust
groove + max magnetic bias +
low oil fill + max disk load/imbalance 3 70 72K 9.5 3.0 1.0
Largest journal gap, thin DLC + max journal groove
depth +max disk load/imbalance + low oil fill 3 70 72K 7.5 4.3 0.75

17. Total Failures by Mode – Customer Integration
35
30
Plan to attack these
25
failure modes in the ORT
20
QTY plan
15
10
A
B
5
C D E
0
Selection of top 5 Field Failure Modes
Data represents a < 5 % FA of all Customer Integration Failures

18. Total Failures by Mode – Field Returns
35
Plan to attack these
30
failure modes in the ORT
plan
25
F
20
G
QTY 15
H
10
5
I J
0
Selection of top 5 Field Failure Modes
Data represents a < 5 % FA of all Field ARR Failures

19. Defining Acceleration Factors
Acceleration factor (AF)is the ratio of the

characteristic life at the use and
accelerated test conditions:
L ( usage stress )
AF
L (accelerate d stress )

20. Multiple Stressor Acceleration Factor Calculation
AF total AF 1 AF 2
Life 1spec ( time )
AF 1
Life 2test ( time )
spec
Life 2 time
AF 2 spec
Life 2 time
Where:
AF1 is the acceleration factor for stressor 1
AF2 is the acceleration factor for stressor 2
Lifespec – the motor life per specification

21. Typical Stressors
• Variable Speed profile
• Time/Number of Cycles
• Temperature
• Humidity
• Operating and non operating shock
• Electrical bias
• Load

22. Definition of Failure
Parameter
A failure is defined as a significant change in the motor
performance parameter over time/cycles.

23. Capillary Seal Non-operating Shock Analysis
Capillary Seal Analysis Meniscus Surface Area Calculation
Shock
direction
Shock direction

24. Capillary Seal Fill Process Trade off
Model based
Evaporation limited Gravitational Sag and Shock limited
R a d ia l G a p

25. Capillary Seal Gap Design Trade off
Model based
Evaporation limited Gravitational Sag limited
R a d ia l G a p

26. Oil Sag due to gravity, margin to fill hole
Seal Volume(ul) : 3.32 Seal Volume(ul) : 3.5 Seal Volume(ul) : 3.68
300 300 300
250 250 250
200 200 200
150 150 150
100 100 100
50 50 50
0 0 0
0.2 0.25 0.3 0.35 0.4 0.2 0.25 0.3 0.35 0.1 0.15 0.2 0.25 0.3 0.35
Sag Margin millimeters Sag Margin millimeters Sag Margin millimeters

27. Autocatalytic Reactions
• An Autocatalytic reaction is the reaction where the product of the
reaction is also a reactant.
• The approach to an autocatalytic rate equation:
A B
v kAB
and
A A x
o
B B x
o o
so
dx
kA x P x
The rate of Change in concentration of the component(s) in an
o o
dt
and
autocatalytic reaction and is described through
at the logistic equation
x e 1
at
P o 1 be
where
a A P k
o o
P o
b
A o
27

28. Sigmoid Logistic Curve
• In Case of the oil (ester) hydrolysis which is auto catalyzed by acids:
RCO2R’ + H2O → RCO2H + R’OH (a)
RCO2R’ + RCO2H + H2O → 2 RCO2H + R’OH (b)
• The general rate change equation of the autocatalytic reaction:
Autocatalysis Logistic Curve
at
x e 1 12
at
Po
Normalized Concentration change x/[P]o
10
1 be
where 8
a A P k 6 Logistic Curve
o o
P o
b 4
A o
2
0
0 2 4 6 8 10 12 14
Adjusted Time Unit ([A]o+[P]o)kt
28

29. Run Current Analysis of the Lubricant Hydrolysis
• Assume linear dependence
between the Irun and the
concentration increase of
the hydrolysis reaction.
• Fit the Logistic Curve into I run
f (t )
o
the existing Irun versus I run
time equation:
or
I run exp( kt ) 1
o
I run 1 k 2 exp( kt )
29

30. Understanding Wear
• Wear is the erosion of material from a solid surface by the action of another solid.
There are four principal wear processes:
1. Adhesive wear
2. Abrasive wear
3. Corrosive wear
4. Surface fatigue
• Also wear can be classified as dry wear, semi-lubricated wear and lubricated (wet)
wear.
• Wear is a complex phenomenon that is a result of generation of thermal or/and
chemical energy.
• Wear in the bearing is generated as a result of the contact forces acting between
the wear couple components. The work of wear can be calculated from the
relation below if the spin down profiles and the forces acting on the bearing
components are known. We assume that the wear depth is proportional to the
contact pressure in place of contact.

31. Stress Tests to induce failures
Orientation 1 Orientation 2 1
31
27
21
26
22
Hi
Hi
29
30
15
20
Parameter1
Parameter1
10
44
11
16
8
14 5
19
3 28 43
42 13 7
12 18
32
40
37
38 35
24
Low
Low
34
33
Hi Parameter2 Low Hi Parameter2 Low
Induce motor failures by testing beyond customer specifications
Responses: 1. Wear 2. Time to failure
Factors: 1. Parameter 1 2. Parameter 2 3. Parameter 3
Categorical: 1. Orientation
Failures are marked in red

32. Typical Wear Rate
Wear rate vs. sliding distance
Wear Rate
L
Contact (sliding) Distance
Assume that the wear coefficient is a constant (average wear
coefficient) for a given material pair to simplify wear
experiments.

36. Critical Parameter Scorecard
P NC a n
S c ard
Top
S L D M
79 Ana lyst: P a ra m e te r
# CTQ 's
21 Tota l
Progra m
M a turity Le ve l < 2
Da k ota /Fire bird - Nide c _ DLC De s ign 21
Us e r In p u t
Gu id e Z Mar
21 M issing ZST
Sc ore c a rd
M issing G a ge %(P /P )
21 Z M a rgin
Ne w CTQ Na m e
21 <0
La s t Upda te d In p u t L o n g T e r m M e an an d Std De v
M e n u Gu id e
De fa ult M a turity Le ve l
(fo r No r m al Data) OR L o n g T e r m PNC
11-O ct-04 21 0.0 to 0.5
(fo r No n -No r m al/A ttr ib u te d ata) 21 De fa ult Thre shold ZST > 0.5
Sea g a te C o n fi d en ti a l Re v 6.0
Thre shold
Low e r Uppe r S ta nda rd G a ge M a turity
CTQ Na m e Units Mean P NC P NC ZST
De via tion %(P /P ) Le ve l ZST
S pe c Lim it S pe c Lim it
> P e rform a nce
> Ele ctrica l
P aram eter 1
P aram eter2
P aram eter3
P aram eter3
P aram eter4
P aram eter5
P aram eter6
> M e cha nica l
P aram eter 1
P aram eter2
P aram eter3
P aram eter3
P aram eter4
P aram eter5
P aram eter6
> Re lia bility
P aram eter 1
P aram eter2
P aram eter3
P aram eter3 - -
P aram eter4
P aram eter5
P aram eter6 - -
- -

37. Summary
• A successful implementation of Design for Reliability (DFR)
approach in high volume spindle motor development and
manufacturing demonstrated a significant benefit in
identifying and addressing critical failures and accelerating
design stages.
• We have developed, validated and implemented a number
of physics and DOE based predictive reliability models to
address the design CTQ early in the concept phase.
• In addition to this, a suite of highly accelerated stress tests
was successfully developed to identify critical failure modes
in the prototype build stages.