View
241
Download
5
Tags:
Embed Size (px)
Citation preview
MPD 575MPD 575
Design for ReliabilityDesign for Reliability
Jonathan Weaver
2
DReliability Development History
• Originally developed by MPD Cohort 3 team of Julie Earle, Dave Herczeg, and Jim Van Gilder in Fall 2002.
Design for Reliability
Design for Reliability
4
Why Design for Reliability?
• Reliability can make or break the long-term success of a product: – Too high reliability will cause the product to
be too expensive– Too low reliability will cause warranty and
repair costs to be high and therefore market share will be lost
5
What is Reliability?
• Reliability is:• Elimination/avoidance of failure modes/mistakes • The probability that a product will perform its intended
function: • Under customer operating conditions • For a specified life • In a manner that meets or exceeds customer expectations
• A reliable product is robust and mistake-free
6
• Probability is:• a measure that describes the chance or
likelihood that an event will occur. • The probability that event (A) occurs is
represented by a number between 0 (zero) and 1. • When P(A) = 0, the event cannot occur.
• When P(A) = 1, the event is certain to occur.
• When P(A) = 0.5, the event is as likely to occur as it is not.
What is Probability?
7
Reliability Failure Modes
Two types of failure mode:a) hard = something breaksb) soft = performance degrades
Two root causes:1. lack of robustness (sensitivity to noise factors)2. mistakes
8
What are Noise Factors?
• Noise Factors are sources of disturbing influences that can disrupt the ideal function, causing error states which lead
to quality problems.
9
• A population is:• The entire group to be studied (e.g. all Ford Contours)
• A sample is:• A subset of a population selected randomly for analysis (e.g., every hundredth Ford Contour off the assembly line)
What is Population and Sample Size?
10
Common Measures of Unreliability
• % Failure - % of failures in a total population
• MTTF (Mean Time To Failure) - the average time of operation to first failure.
• MTBF (Mean Time Between Failure) - the average time between product failures.
• Repairs Per Thousand (R/1000)
• Bq Life – Life at which q% of the population will fail
11
Introduction to DFR
• DFR has many aliases:– Design for Durability– Design for Robustness– Design for Useful Life
12
When to Use DFR
• DFR should be considered throughout the PD cycle:
• Early - to develop "product concepts" which are well suited for production (i.e., conceptual product design)
• Continually - to ensure that the chosen product concept is implemented through optimal component design
13
Automotive Reliability Facts
• The shortest route to higher satisfaction is not only through the dealership service department –
it is mainly through keeping customers out of the service department in the first place.
• Customers who report zero problems with their new cars have an owner loyalty rate of 73 percent and dealer loyalty of 42 percent.• At 4 TGW, loyalty to the company drops by 1/3 to 44%,
while loyalty to the dealer drops to zero.
14
Automotive Reliability Facts
• The average age of a purchased vehicle at
the time of replacement is 5.7 years in the
U.S. and 4-5 years in Europe.
• The average lifetime of a vehicle before scrap
is 12.7 years in the U.S. and 10 years in
Europe.
15
Steps in Designing for Reliability
1. Develop a Reliability Plan• Determine Which Reliability Tools are
Needed
2. Analyze Noise Factors
3. Tests for Reliability
4. Track Failures and Determine Corrective Actions
16
1. Develop a Reliability Plan
• Planning for reliability is just as important as planning for design and manufacturing. Why? To determine: • useful life of product• what accelerated life testing to be used • where to begin
• Reliability must be as close to perfect as possible for the product’s useful life.
17
• A Reliability Plan helps ensure that product reliability is optimized within the cost and performance constraints of a program and customer requirements.
1. Develop a Reliability Product Plan
18
1. Develop a Reliability Plan
• How much reliability do you need? Should you accelerate life testing? Where do you even begin?
• Planning for product reliability is just as important as planning for product design and manufacturing.
• The amount of product reliability must be in proportion to a product's usage and warranty goals. Too much reliability and the product will be too expensive. Too little reliability and warranty and repair costs will be high.
• You MUST know where your product's major points of failure are!
19
Some Reliability Tools
• Block Diagram• P-Diagram• QFD• DFMEA & PFMEA• Design Verification Plan
– Key Life Testing– Weibull Testing
• Reliability Demonstration Matrix
20
Reliability Block DiagramThree categories:
•Series •Parallel (Redundant)•Complex (combo of the two – shown below)
21
P-Diagram
System
NoisesOutputs
error states/failure modes
Input
Control Factors
Signal(energy related)(energy related)
IDEAL Response
22
Technical System Expectations
Relationship MatrixCustomer Wants Customer TargetsCustomer
Competitive Evaluations
Technical Importance
Technical Targets
Technical Competitive
Benchmarking
Safety & RegulatoryReqmts Matrix
WCR/SDS MatrixWCR/SDS
Safety & RegulatoryReqmts S
tds
Std
s
Strategic CDICustomer Desirability Index
Technical Axis
Customer Axis
Quality Function Deployment
23
FMEAs
• Potential Failure Mode
• Potential Effects of Failure
• Severity
• Classification
• Potential Cause/Mechanism of Failure
• Occurrence
• Design Controls (Prevention/Detection)
• Detection• Risk Priority Number• Recommended Actions• Responsibility/Target Completion
Date• Actions
24
DVP&Rs
• Test Specification
• Acceptance Criteria
• Test Results
• Design Level
• Quantity Required
• Quantity Tested• Scheduled Start/
Complete• Actual Start/ Complete• Remarks
25
Reliability Demonstration Matrix CD132 ELECTRICAL SUNROOF SYSTEM Updated: July 09, 1999
ROBUSTNESS and RELIABIL ITY CHECK LIST Kick-off :
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
cu
sto
me
r d
uty
cyc
le
wa
ter
manag
m.E
/E d
ev.
ele
c.
devic
e c
onn.
orie
nt.
co
lor
codin
g i
den
tifi
cati
on
PIA
wir
e a
sse
m.
co
mp
.
str
es
s c
rac
k.
f. p
las
tic
s
wa
ter
leak
age
se
als
win
dnois
e w
indow
clo
sed
op
era
ting s
ou
nd
ap
peara
nc
e a
gein
g
forc
ed e
ntr
y
sm
oo
th o
per.
& t
rackin
g
po
sitio
n s
tabili
ty
reg.
des
s
td.
sta
ll fo
rce w
ith a
uto
re
v
reg.d
es
.std
.gla
zin
g.m
ate
rials
sy
ste
m p
erf
orm
. ov
er
vo
ltag
e
tem
pera
ture
diff
. g
laz
ing
win
dnois
e &
win
d t
hro
b/
buff
etin
g
ve
loc
ity
moon
oof
pa
ne
l
ERROR STATES -- potential TGW and/or "Noises" for other sub-systems (detail description) Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
VII Sunroof produce not acceptable windnoise (closed: windnoise, open: buffeting) VII NOISE FACTOR MANAGEMENTVI Sunroof rattles, sqeaks VIV Water management is insufficient V Cat Strategy M
R-0
00
2
ED
- 0
04
0
ED
- 0
04
0
ED
- 0
08
1
ED
- 0
07
7
IT11
6
MG
- 0
00
8
MG
- 0
00
9
MG
- 0
01
2
MG
- 0
01
3
MG
- 0
01
8
MG
- 0
01
9
MG
- 0
00
6
MG
- 0
03
0
MG
- 0
03
1
MG
- 0
03
3
MG
- 0
03
8
MR
-00
07
MR
-00
1
IV Sunroof seal comes away IV A Change TechnologyIII Anti Pinch device doesn't work proper III BI Apply Parameter DesignII Sunroof binds on rear edge II BII Upgrade Design Spec.I Sunroof doesn't operate proper (jamming, judder, no smooth movement) I C Reduce / Remove Noise
D Add Compensation DeviceE Disguise / Divert
Strategy10 NOISE 1: TOTAL DESIGN / MANUFACTURING VARIABILITY I II III IV V VI VII used Specifics applied (describe)11 Piece-to-piece variation or a) gear assy single parts variation x x x x C;A SPC on crit dim, encaps. glass I;VI I I VII I I I III I I VII I
drawing tolerance, b) gear assy assembly variation (PTA, Webasto) x x x x x C SPC on crit dim. I;II;V V I I III I VII Iwhichever is greater, and c) BIW component variation (single parts) x x x x A encap. glass I;II V VII VIItotal scope applicable d) BIW assembly variation (Body Construction) x x x x x A encap. glass I;II V VII III VII
e) BIW paint variation x x x x A Modified seal I;II IIIf) vehicle interior trim component variation x A new edge trim designg) vehicle interior trim assembly variation x A new edge trim designh) sunroof assembly variation (PTA, Genk) x x x x x x A new locator strategy I VII III VII
20 NOISE 2: COMPONENT CHANGES OVER TIME / MILEAGE -- over Useful Life Period21 Change in dimension or a) gear assy component wear x x x C,A SPC on crit dim., new s/r frame I;VI VII I I I VII I
(assumptions above) d) BIW stiffness degradation x BII Reinforce BIWe) vehicle interior trim fatique (fixing) x BII Upgrade interior trim fixings I;VIf) paint surface wear x BII Use harder paint VI
30 NOISE 3: DUTY CYCLE / CUSTOMER USAGE -- over Useful Life Period
31 "Typical" a) high frequency use x x BII using SDS instead of ES spec I;VI I ICustomer usage b) vehicle speed x x C,A SPC on crit dim., new s/r frame VII III VIIover Useful Life Period c) sunroof misuse (override), only on mechanical system x BII using SDS instead of ES spec I(assumptions above) d) external roof load x BII Change anti trap parametrisat. III
e) road profile x x A new s/r frame tech. VI IIIanti trap usage x x BII WDS instead of EWG74/60 I;III
32 Transport, storage, dewaxingf) non-usage N/A33 High pressure cleaning g) cleaning water / chemicals, high pressure jet x BII using SDS instead of ES spec IV;V35 Customer misuse/abuse i) neglect poor service, uncontrolled fluids N/A No service necessary
40 NOISE 4: EXTERNAL ENVIRONMENT
41 Climatic conditions, Typical territory Condition 1 Condition 2geographic conditions, a) Canada, Scandinavia cold dry x x x x BII using SDS instead of ES spec I;IV;VI I III Ilocal environment, b) Britain, Germany cold humid x x x x x BII using SDS instead of ES spec I;IV;VI I I III Isurfaces or obstacles, c) Arizona, Florida, AUS sunload dry BII using SDS instead of ES spec I III Iramps and curbs, d) Taiwan hot wet x x x BII using SDS instead of ES spec I;VI I I III Iindustrial fall-out, e) Nova Scottia salt x BII using SDS instead of ES spec I I I IIIinsects, trees... droppings, f) Pikes Peak, GGlockner high altitude long downhillmarten bite etc. g) industrial fall out, trees dropping, dust, dirt, BII using SDS instead of ES spec I;IV
50 NOISE 5: IN-VEHICLE SYSTEMS ENVIRONMENT -- over Useful Life Period
51 Physical interfaces a) generic passenger compartment seal conditions x BII Change winddeflector design VII VIIwith associated systems b) torsional stiffnes of different body styles x BII Reinforce weakest BIWor mating components c) suspension type/ tires of different derivatives x BII Increase sunroof S&R robust.over Useful Life Period d) passenger comp. volume of different body styles x BII Change winddeflector design VII
52 Loads from or f) vibration x x BII using SDS instead of ES spec I;VI IIIinteraction with g) EDS voltage variation x BII using SDS instead of ES spec I III I Ineighboring systems h) electromagnetic field BII using SDS instead of ES spec III
Design Controls, CAD / CAE ... Component => Subsystem ==> System ===> Vehicle Tests
Useful L ife Period Target
10 Years or 240,000 km (or 13,000
cyc les)
20 21 22 23 24 25 Ref.
slid
ing s
had
e o
pe
r. e
ffo
rt
slid
ing s
had
e b
reak
aw
ay
effo
rt
reg.d
es.
std.f
lam
abili
ty o
f in
t. m
atr
ls.
reg
.de
s.st
d.o
ccu
pa
nt p
rot.i
nt.i
mp
.
sun
roo
f a
sse
mb
ly&
fun
ct.t
est
PA
SC
AR
Te
st
Y Y Y Y N N
/ d
MR
-00
16
MR
-00
17
MR
-00
31
MR
-00
32
o r
N ad
T n
S a
E t
T S
I I II I II;IV
II;IVII;IVII;IV
I II I
II;IV
I IVIVIVI
I I
I II I II;IVI II II I
VIVI
Design Controls, CAD / CAE ... Component => Subsystem ==> System ===> Vehicle Tests
Test
Descrip
tio
nIs
th
is t
es
t in
clu
de
d in
DV
P ?
Y o
r N
(Y
es
/ N
o)
En
ter
IF, I
F2
, IF
3 ..
. (fo
r "I
de
al F
un
ctio
n/s
") a
nd
/or
A, B
, C ..
. (fo
r "E
rro
r S
tate
/s")
mo
nito
red
or
me
asu
red
in e
ach
ind
ivid
ua
l te
st
Potential Failure modes
Noises #1Noises #2Noises #3Noises #4Noises #5
Available TestsN
ois
e t
o f
ailu
re
mo
de
tra
cea
bili
ty
No
ise
fa
cto
r m
ana
gem
ent
str
ate
gy
Failure mode to test traceability and
Noise factor to test traceability leading to ...
Reliability & Robustness Demonstration
“In the development of robustness, it is essential to provide one noise condition for each failure mode”. Don Clausing, Professor of Engineering, MIT.
Robustness Assessment and Noise Factor Management Matrix
26
Reliability Demonstration Matrix
1000 10000Failure cycles
Prob
abili
ty
Light Calcium
Heavy-Hi Calcium (c)
Heavy CAG (p)
Heavy CAG Plus
0
1
(c) Current EU(p) Proposed EU
current target proposed target Lucas Yuasa in Toy ota
B10
0.1
2400 5700
Robustness Window
Number of test cycles200 400 600 800
Displa
ceme
nt un
der 6
kN lo
ad
current designmodified design
Note: failure modes 1.1 & 1.2 generate functional degradtion as illustrated.
Battery Suspension bushing
Robustness Demonstration
27
2. Analyze Noise Factors
• Inner Noises• Wear-out or fatigue• Piece-to-piece variation • Interfaces with neighboring
subsystems• Outer Noises
• External Operating Environment (e.g., climate, road conditions, etc.)
• Customer usage / duty cycle
28
2. Reduce Sensitivity to Noise Factors
1. Change the design concept2. Make basic current design
assumptions insensitive to the noises – design out failure
• Parameter Design• Beef Up Design
3. Insert a compensation device4. Disguise the effect - Send the error
state/noise where it will do less harm
29
2. Noise Factor Management 1. 2. 3. 4. 5.Change (i)Parameter (ii)Beef-up Reduce Comp- DisguiseConcept Design. Design Noise ensate
Piece-to-piece x x x
Wear Out x x x
Customer Use x x x
External Environment x x x
System Interactions x x x x
30
3. Test for Reliability• How robust are the products?
– Test to Bogey: assessing performance at a predetermined time, cycle or number of miles. It estimates the proportion of failures at a particular time. pass/fail
– Test to Failure: shows when a component or system can no longer perform at a specified level
– Degradation Testing: focuses on the key stresses associated with real world uses – for example - increasing the tire load to create a tire failure
• How can you shorten the reliability test time for new designs?– Key Life Test/Accelerated Test
31
3. Example – Testing for Reliability• Proportional Hazard Model to Tire Design
Analysis– Perform Root cause analysis
• Consists of laboratory tests aimed to duplicate field failures
• Tire geometry and physical properties are selected as variables that potentially affect the tire
• Survival data is analyzed by a proportional hazard model
– The adequacy is assessed by the chi-square goodness- of fit test and the Cox-Snell residual analysis
• Identify elements of a tire design that affect the probability of tire failure due to failure mode in question.
32
3. Example - Testing for Reliability Cont’d
• Type of failure mode analyzed – tread and belt separation
33
3. Example - Testing for Reliability Cont’d
• Tread and belt separation can be considered a sequence of two events:– Failure crack initiation in the wedge area– Crack propagation between the belts
• Design characteristics that could be variables:– Tire age– Wedge gauge– Interbelt gauge – End of belt # 2 to buttress– Peel force– Percent of carbon black (chemical in rubber)
34
3. Example - Testing for Reliability Cont’d
• Testing procedure– Dyno testing
• Warm up over 2 hours at 50 mph• Cool down over 2 hour at full stop• At 1300 lbs of load: speed steps starting at 75
mph and increasing by 5 mph every half hour till 90 mph and then every hour till failure
• At 1500 lbs of load: all the above speed steps are half-hour duration
35
3. Example - Testing for Reliability Cont’d
• Test speed profile
36
3. Example - Testing for Reliability Cont’d
• Vibration and sound pattern of tire before tread and belt separation failure
37
3. Example - Testing for Reliability Cont’d
• Test data set used in proportional hazard analysis
38
3. Example - Testing for Reliability Cont’d
• Estimates of proportional hazard model with covariates identified
39
3. Example - Testing for Reliability Cont’d
• Estimates of Proportional Hazard Model with statistically significant covariates
40
3. Example - Testing for Reliability Cont’d
• Exponential probability plot of Cox-Snell Residuals
41
3. Example - Testing for Reliability Cont’d
• Cumulative Hazard function predicted from the estimated model based on some typical values of covariates for “poor” and “good” tires
42
3. Example - Testing for Reliability Cont’d
• Conclusion– Wedge and interbelt gauges as well as the
peel force are significant factors affecting hazard rate of tire and belt separation failures in an inversely proportional way
– Agree with hypothesis
43
• Component design and manufacturing technologies are becoming increasingly complex.
• As geometries shrink and development cycles shorten, opportunities for defects increase.
• Testing for Reliability is becoming increasingly important.
3. Test for Reliability
44
• This process involves:• Data collection and selection
• Set up databases for tracking failures• Warranty, Early Warranty, Things Gone Wrong
• Analyzing trends
• Performing closed loop analysis/corrective action
• Calculating observed reliability parameters
• Assessing reliability growth.
4. Track Failures and Determine Corrective Actions
45
4. Track Failures and Determine Corrective Actions
• Brake warranty is on track with targets and achieves more than 60% warranty CPU reduction since 1994
• Brake health charts were instituted in 1995 to monitor key performance index and drive design competency
• Supplier business unit reviews (BURS) quarterly to address key quality and manufacturing issues
$52
$14 Target
$38
$75
$18
$28
$31
$35
$75
$25 Target
$0
$25
$50
$75
$100
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Model Year
$(CPU)
TargetActions Implemented And/ Or ApprovedOld Target
BrakeHealthChart
Created
BrakeQuartback
TeamStarted
FirstFSS/SI
ProgramLaunched
NA 3/36 Combined Car & Truck Brake Warranty CPU Reduction
46
• Time-to-Failure Curve
4. Track Failures and Determine Corrective Actions
47
Challenges in DFR
• Many CAE models have limited capability to represent real-world noise; therefore, surrogate noise based on engineering knowledge is required.
• Precise reliability estimates require precise knowledge of statistical distributions of noise factors.
– As a contrast, comparative reliability assessments and robust design require only approximate knowledge of statistical distributions.
48
Challenges in DFR
• Many CAE models are computationally expensive – preparation time to set up the model – computing time
• Many CAE models focus on “error states” (e.g., fatigue, vibration, noise); therefore, a multi-objective optimization is often needed.
• In early product development, when the impact of robust design can be greatest, design objectives and constraints are still imprecise.
49
References
• Reliability - Ford Design Institute• Ford Reliability Class – T. P. Davis, V. Krivtsov/
VKRIVTSO• http://www.reliabilityanalysislab.com/
ReliabilityServices.asp
• U.S.: R.L. Polk Vehicles in Operation Report June, 1997 Europe: New Car Buyer StudyEuropean Buyer - Big Five Survey 1995
• Ford's Strategy in Reliability (Prof. Tim Davis)
• http://pms401.pd9.ford.com:8080/arr/concept.htm