Design for Reliability Approach in Magnetic Storage Industry

A. Parkhomovsky, R. M. PelstringReliability Engineering, Motor Design Division,

Seagate Technology

Outline• Introduction 

i. Early Reliability Failure Detectionii. Design for Reliability Approach

• Reliability Risk Assessmenti. FMEAii. Fault Tree Analysis

• Predictive Reliability Modelingi. Understanding of physical processes in the productii. Identification of critical to reliability parameters and possible failure modesiii. Design for Reliability Modeling using DOE and first principles approachiv. Reliability Risk Assessment using predictive models

• Customized Accelerated Stress Tests• Summary

Spindle Motor Cross SectionSpindle Motor Cross Section

Journal Bearing

SleeveShaft

Journal Gap

Hub

Design for Reliability Definition

• The tool set that supports product and process design (during the Product Development Cycle) to ensure customer expectations for reliability are fully met.

• Initial

• After Current Stressing

Tk

E

n

a

eJ

ALife sticCharacteri

DFSS vs. DFR

DFR focuses on achieving high quality over time and across stress levels.

DFSS DFR

VOC

MSA

DOE

Control Plans

ANOVA

QFD

FMEA

Regression Flowdown

Environmental & Usage Conditions

Life Data Analysis

Physics of Failure

Accelerated Life Testing

Reliability Growth

Warranty Predictions

FA recognition

General Linear Model

Tolerancing

Sensitivity Analysis Modeling

Hypothesis Testing

Identify and Design

Optimize

FMEA

S = ?O = ?E = ? Fault

Tree

Critical to Reliability Parameters (CTR) and Supplier Capability

ReliabilityModels

StatisticalReliabilityPrediction

Scard79 Analyst: # CTQ's

Program 3

3Scorecard 3

Reliability 3Last Updated 3

3Seagate Confidential Rev 6.0 3

Lower UpperSpec Limit Spec Limit

Motor SeizureDrive Performance FailureDrive Contamination

CTQ Name Units Mean PNCStandard Deviation

Gage %(P/P)

PNC ZSTMaturity

Level

Default Threshold ZST

Menu GuideInput Long Term Mean and Std Dev

(for Normal Data) OR Long Term PNC

(for Non-Norm al/Attribute data)

New CTQ NameDefault Maturity Level

Missing ZST

Missing Gage %(P/P)

Parameter

Total

User Input

Guide

Maturity Level < 2

Top DTop L MDS

Design for Reliability

Validate

• Motor Design Limits Testing

• Concept Verification

Control

SPC

Post-TransferControl MeasuresVerify

System Margin and Robustness

Product Development and Life Cycle Process

Design For

Reliability

Reliability Verificatio

n

Product and Process Analysis

• Physics of Failure understanding and modeling

• FMEA, design risk analysis, Fault Tree

• Design, process and product analyses

• Failure Analysis

• Early Reliability Tests

• Design Limit Tests

• Field Data analysis

Gap Closure though interrelated concurrent activities

Ensuring Reliability in the Product Development Process

Concept

Evaluation

Design Maturity

Transition

ProductionProduct

Development

Phases

Fault Tree, FMEA,

Design Rules

Early Reliability Tests

Reliability Limit Tests

Reliability Limit Tests

Ongoing Reliability

Tests

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

Design for Reliability Approach Strategies

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.

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.

Comparative Resource Commitment

Actual Resource

Level

Post ReleaseProblem Teams

Time

Planned Resource Level

Reso

urce

Lev

el

Expected Resource Levelwith Design for Reliability

Many Changes Few Changes

Shorter Development CyclesEfficient Use of Resources

Reliability Model Feedback LoopEvent Reduced fly height EventDescription DescriptionCond PNC 1 Cond PNC 1Cum PNC 0.0001 Cum PNC 0.0001Function AND Function AND

Event Wear occurs in CP grooves EventDescription DescriptionCond PNC 0.0001 Cond PNC 0.0001Cum PNC 0.0001 Cum PNC 0.0001Function AND Function AND

Event Contact occurs in thrustDescriptionCond PNC 1Cum PNC 1Function AND

EventDescriptionCond PNC 1Cum PNC 1Function

Event Op ShockDescription 1000 g'sPNC 1Function

DLC contamination causes wear / seizure

Contact stress exceeds DLC strength

Restoring force does not prevent contact

Product

Op-shock

250 g’s 2 ms

MobileMarket Requirement

Fault Tree Analysis

Design opportunity and model gap identified to “break” failure chain.

24.524.023.523.0

300

200

100

0

Force Distribution

Fre

qu

ency

Histogram of Force Distribution

1.585 1.595 1.605 1.615 1.625 1.635

0

100

200

Stress

Fre

qu

ency

Histogram of Stress

Model Developmentand Results

FImpact scontact

DesignImprovement

Contact relief to reduce contact stress.

Fault Tree Model – Shock Failure

Fault Tree general skeletons are developed, then they are easily adapted to the particulars of each design.

FMEA – Test Linkage: Example

Motor Design FMEAItem Part Potential Failure Mode Effects of Failure S Potential Cause O Design Verification E RPN

11 Sleeve/ Thrust Cup assy

excessive wear on thrust surface

motor seizure 10 High runout, contamination (ECM)

2 runout measurement 2 40

15 Bearing assemblycomponents rubbing while spinning motor lock up, oil leakage 9

parts tolerance allow contact or not meeting print.

4

Min Gap model includes all surface and diameter parameters, bearing drag test will be correlated to journal gap.Performance testing.

1 36

18 Bearing assembly journal wearchange in performance, oil degradation, motor lock up & oil leak from gyro test

8wear from operating tests, gyro scopic wear, CSS

5design validated through testing and run more that 60k cycles 2 80

23 EM EM bias force too highreduced fly height, increased wear rate 5

Misalignment of stator, magnet or bias ring. Incorrect magnetization

2In-process height measurements, drawings/tolerance studies, magnetization

3 30

The Design FMEA is developed based on critical failure modes from the fault tree analysis.

Motor Reliability Design Limit Test (RDLT) Plan Test Test Groove Depth Shaft DLC

FMEA Duration Test Test Orientation Temp. CSS Thrust Journal Thickness

Savvio Motor Design Variables Item # RPN # (month) Qty +VSA -VSA HSA ( 0C ) (cycles) (mm) (mm) (mm)

Motor Wear Test 11,15,18,23 81 2 15

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

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.

Design Limits Test Development

Total Failures by Mode – Customer Integration

Data represents a < 5 % FA of all Customer Integration Failures

0

5

10

15

20

25

30

35

Failu

re M

ode1

Failu

re M

ode 2

Failu

re M

ode 3

Failu

re M

ode 4

Failu

re M

ode 5

Failu

re M

ode 6

Failu

re M

ode 7

Plan to attack these failure modes in the ORT

plan

AB

C D E

QTY

Selection of top 5 Field Failure Modes

Total Failures by Mode – Field Returns

Data represents a < 5 % FA of all Field ARR Failures

0

5

10

15

20

25

30

35

Failu

re M

ode 1

Failu

re M

ode 2

Failu

re M

ode 3

Failu

re M

ode 4

Failu

re M

ode 5

Plan to attack these failure modes in the ORT

plan

HG

I J

F

QTY

Failu

re M

ode 6

Failu

re M

ode 7

Selection of top 5 Field Failure Modes

Defining Acceleration Factors

)(

)(

stressdaccelerateL

stressusageLAF

Acceleration factor (AF)is the ratio of the characteristic life at the use and accelerated test conditions:

Multiple Stressor Acceleration Factor Calculation

21total AFAFAF *=

)(

)(

2

11 timeLife

timeLifeAF

test

spec

timeLife

timeLifeAF

spec

spec

2

22

Where:

AF1 is the acceleration factor for stressor 1

AF2 is the acceleration factor for stressor 2

Lifespec – the motor life per specification

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

A failure is defined as a significant change in the motor performance parameter over time/cycles.

Definition of FailureP

aram

eter

Capillary Seal Analysis Meniscus Surface Area Calculation

Shock direction

Shock direction

Capillary Seal Non-operating Shock Analysis

Capillary Seal Fill Process Trade off

Gravitational Sag and Shock limitedEvaporation limited

Radial GapRadial Gap

Model based

Capillary Seal Gap Design Trade off

Model based

Gravitational Sag limitedEvaporation limited

Radial GapRadial Gap

Oil Sag due to gravity, margin to fill hole

0.2 0.25 0.3 0.35 0.40

50

100

150

200

250

300

Sag Margin millimeters

Seal Volume(ul) : 3.32

0.2 0.25 0.3 0.350

50

100

150

200

250

300

Sag Margin millimeters

Seal Volume(ul) : 3.5

0.1 0.15 0.2 0.25 0.3 0.350

50

100

150

200

250

300

Sag Margin millimeters

Seal Volume(ul) : 3.68

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:

o

o

oo

oo

oo

o

A

Pb

kPAa

where

and

xPxAkdt

dx

so

xBB

xAA

and

BAkv

BA

atbe

ate

oPx

1

1

The rate of Change in concentration of the component(s) in an autocatalytic reaction and is described through

the logistic equation

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:

o

o

oo

A

Pb

kPAa

where

atbe

ate

oPx

1

1Autocatalysis Logistic Curve

0

2

4

6

8

10

12

0 2 4 6 8 10 12 14

Adjusted Time Unit ([A]o+[P]o)kt

No

rmal

ized

Co

nce

ntr

atio

n c

han

ge

x/[P

]o

Logistic Curve

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 the existing Irun versus time equation:

)exp(1

1)exp(

)(

2 ktk

kt

I

I

or

tfI

I

orun

run

orun

run

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 wear4. 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.

Low

Par

amet

er3

Hi

33

24

28

20

42

30

31

22 26

3840

44

Hi Parameter2 Low

Lo

w

Pa

ram

ete

r1

H

i

Orientation 1

14

12

8

183

34

35

19

15

43

29

1

21 27

3732

1016

13

11

75

Failures are marked in red

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

Stress Tests to induce failuresOrientation 2

Lo

w

Pa

ram

ete

r1

H

i

Hi Parameter2 LowLow

P

aram

eter

3 H

i

Typical Wear RateWear rate vs. sliding distance

Contact (sliding) Distance

We

ar

Rat

e

L

Assume that the wear coefficient is a constant (average wear coefficient) for a given material pair to simplify wear

experiments.

Critical Parameter ScorecardScard

79 Ana lyst: # CTQ's

Program 21Dakota/Firebird - Nidec_DLC Design 21

Scorecard 2121 Z Ma rgin

Last Updated 21 < 011-Oct-04 21 0.0 to 0.5

Sea ga te Confidentia l Re v 6.0 21 > 0.5Low e r Uppe r

Spe c Lim it Spe c Lim it> Pe rform a nce> Ele ctrica lParameter 1Parameter2Parameter3Parameter3Parameter4Parameter5Parameter6

> Me cha nica lParameter 1Parameter2Parameter3Parameter3Parameter4Parameter5Parameter6

> Re lia bilityParameter 1Parameter2Parameter3Parameter3 - -Parameter4Parameter5Parameter6 - -

- -

Thre shold ZST

PNC a nd ZST Ca lcula tor

Pa ra m e te r

Tota l

Us e r Input Guide

Ma turity Le ve l < 2

Missing ZST Z Ma rgin Sum m a ryMissing Ga ge %(P/P)

M e nu GuideInput Long Te rm M e an and Std De v

(for Norm al Data) OR Long Te rm PNC (for Non-Norm al/Attr ibute data)

Ne w CTQ Na m eDe fa ult Ma turity Le ve l

De fa ult Thre shold ZST

CTQ Na m e Units Me a n PNCSta nda rd De via tion

Ga ge %(P /P)

PNC ZSTMa turity

Le ve l

Top DTop L MDSScard

79 Ana lyst: # CTQ's

Program 21Dakota/Firebird - Nidec_DLC Design 21

Scorecard 2121 Z Ma rgin

Last Updated 21 < 011-Oct-04 21 0.0 to 0.5

Sea ga te Confidentia l Re v 6.0 21 > 0.5Low e r Uppe r

Spe c Lim it Spe c Lim it> Pe rform a nce> Ele ctrica lParameter 1Parameter2Parameter3Parameter3Parameter4Parameter5Parameter6

> Me cha nica lParameter 1Parameter2Parameter3Parameter3Parameter4Parameter5Parameter6

> Re lia bilityParameter 1Parameter2Parameter3Parameter3 - -Parameter4Parameter5Parameter6 - -

- -

Thre shold ZST

PNC a nd ZST Ca lcula tor

Pa ra m e te r

Tota l

Us e r Input Guide

Ma turity Le ve l < 2

Missing ZST Z Ma rgin Sum m a ryMissing Ga ge %(P/P)

M e nu GuideInput Long Te rm M e an and Std De v

(for Norm al Data) OR Long Te rm PNC (for Non-Norm al/Attr ibute data)

Ne w CTQ Na m eDe fa ult Ma turity Le ve l

De fa ult Thre shold ZST

CTQ Na m e Units Me a n PNCSta nda rd De via tion

Ga ge %(P /P)

PNC ZSTMa turity

Le ve l

Top DTop L MDS

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.