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Questions and Answers
How Relevant Questions
Obtain
Useful Answers
Judson B. Estes
Fiat Chrysler Automobiles
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
1
Focus on the 4 C’s
Weave the wisdom from many available tool sets into a package of
training, certification and project work
1.
Collect
Currently available facts relevant to problem.
Listen for what is already known and suspected.
Communicate to entire team the current facts to get on the same page.
2.
Contrast
A Measurable difference in performance.
How do you measure the performance?
How Big is the difference?
3.
Converge
Use Logical Strategies to isolate the candidate cause.
What split are you making?
How does that narrow the possible causes?
4.
Confirm
Test the candidate cause to prove it is the true root cause.
What is your Statistical Confidence?
When can we implement the fix?
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
2
Collect Phase
• Describe Problem
• Identify Possible Causes
• Evaluate Possible Measurements
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
3
Collect Phase
Describe the Problem
• State the Problem naming the deviation for
which you want to find the cause
• To help stay on track, ask:
– What object (or group of objects) has the deviation?
– What deviation does it have?
– What do we see, feel, hear, taste, or smell that tells us there is a
deviation?
– Write a short statement in Object/Deviation format
• Use one object and one deviation
• Be specific, separate if needed
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
4
Collect Phase
Specify the Problem
• Describe the deviation
factually to increase
understanding of the
deviation
• Ask questions in 4 areas:
– WHAT—Identity
– WHERE—Location
– WHEN—Timing
– EXTENT—Size
March 2014
IS
IS NOT
Describe the
problem in
detail.
Tighten IS data.
Help eliminate
possible causes.
Confidential and Proprietary to Fiat Chrysler Automobiles
5
Collect Phase Example
PROBLEM SOLVING
[1]
PROBLEM AREA
Problem Statement:
Description
facts
LX low beam bulb infant failure
PROBLEM ARPEA
NON-PROBLEM AREA
(IS observed / reported)
(IS NOT observed/reported)
WHAT:
1.
Object
low beam bulb # L0009006
used in LX 300 models
LXCH48, LXCP48, LXFP48 .
Click here to see VIN list
Magnums and 300C's. Also WK, PT use
same Pt # low beam bulb, All other bulbs
in the Click here to see ID of vehicle,
subassemblies, bulb and field warranty
performance.
2.
Defect
LOP 085032 Needs
replacement Some examined
from Field, Hot shock is the
main conclusion from the
Sylvania lab report
Other potential lab conclusions could have
been but were not "cold shock", "high
voltage" & "wear out"
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
6
“I often say that when you can measure
what you are speaking about, and express it
in numbers, you know something about it;
but when you cannot measure it, when you
cannot express it in numbers, your
knowledge is of a meagre and unsatisfactory
kind;”
-Lord Kelvin
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
7
Contrast Phase
Frequency
Required
1
0
Current
4
Length (mm)
Frequency
Required
Current
-3
-1.5
0
1.5
3
Flushness (mm)
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
8
Contrast Phase
Open seams on DR
seats resulting in high
warranty costs
Cloth seats
Problem Definition Statement
Front seat
Driver side
Seat back
Rear seat
Seam A
Frequency
71% of returns are driver side seats
92% of returns and narratives are seat cushions
Examination of returned product shows
seam B accounts for 42 out of 54 claims
Seam B
BOB/WOW seam
WOW cushion
March 2014
83% of returns are front seats
Passenger side
Seat cushion
Required
0
90% of returns are leather
Leather seats
1
Other
strategies
See Strategy Diagram
Current
Width (mm)
Find and eliminate the Red X
causing open seams on the DR
front driver side leather seats
4
Confidential and Proprietary to Fiat Chrysler Automobiles
9
Contrast Phase
• What is a BOB and a WOW?
– Best of the Best and Worst of the Worst
– Not necessarily a good and bad part but really
parts that are as different as possible in the
way they effect the Customer.
– We are looking for contrast in order to see
differences
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
10
Contrast Phase example
Measure twice and
get the same answer
on BOB and WOW
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
11
Converge Phase
• Once we make sure our measurement system isn’t
fooling us then we start generating clues
• We then use certain tools to begin to converge on
the Red X candidate
– Concentration diagram
– Component search Stage 1 and 2
– Operation Search
– Paired and Group comparisons
– Event to Energy transform
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
12
Reactive Problem Solving Hierarchy
Use the Right Tool for the Problem
TRIZ and
Systemology
Innovation and Evolution
Pure Statistics
No Strategy and All Tools
Six Sigma
Classical and Taguchi
Design of Experiments
Simple Strategy and Most Tools
Multiple Variables and
Interactions
Shainin Red X Strategies
Multiple Strategies, Easy Statistics
IS/ IS Not Problem Specifications
Distinctions and Changes
Ishikawa Fishbone Diagram
5 Whys to the Root Cause
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
Organized Brainstorming
Simple Questioning
13
Problem Solving Hierarchy
Least Widely Used
Hardest to Grasp
TRIZ and
Systemology
More Variables
and Interactions
Pure Statistics
Six Sigma
Increased
Variation and
Environment
Changes
Classical and Taguchi
Design of Experiments
Shainin
Critical Thinking
Ishikawa Fishbone Diagrams
Most Widely
Used
March 2014
5 Whys to the Root Cause
Confidential and Proprietary to Fiat Chrysler Automobiles
Easiest to
Grasp
14
Concentration Diagram example
1
A
B
C
D
E
F
2
3
4
5
6
7
8
xx
xx
x
x
xx
xxx
xx
xxx
xxx
xxxx
x
Paint Craters on “B” pillar
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
15
Component Search Stage 2
.
• Plotting
Stage 2
30
Stage 1
20
*
10
Green Y = lbs.
WOW
+
*
+
*
*
+
+
+
*
*
+
0
BOB
Orig.
March 2014
1st D/R 2nd D/R 3rd D/R S1
Confidential and Proprietary to Fiat Chrysler Automobiles
orig
16
Confirmation Phase
• Once we identify the Red X candidate it is now time
to use statistics to confirm our candidate.
• Some tools types that are used for this:
– Six Pack B vs. C
– Tukey test
– Barrier B vs. C
– Spike B vs. C
– 5 Penny test
– Factorial Experiment (DOE)
– Binomial probability
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
17
Six Pack B vs. C
• B
• C
B is the “Better” part or
process or sub-assembly or
material
March 2014
C is the “Current” part or
process or sub-assembly or
material
Confidential and Proprietary to Fiat Chrysler Automobiles
18
Six Pack B vs. C Example 1
The required confidence level is 95%, which therefore requires a
sample size of 3 B’s and 3 C’s and an end count of 6.
Rank Order
B
8.3
B
8.8
B
9.1
C
9.8
C
10.6
C
11.2
March 2014
Run Order
B or C
1
C
Diameter
(mm)
10.6
2
B
8.3
3
C
11.2
4
C
9.8
5
B
9.1
6
B
8.8
The end count equals 6. Therefore, it
can be stated with 95% confidence that
the B’s are better than the C’s.
Confidential and Proprietary to Fiat Chrysler Automobiles
19
Six Pack B vs. C Test Example
• Distribution of two groups looks something like this.
B
8.0
March 2014
B
8.5
B
9.0
C
9.5
C
10
10.5
Confidential and Proprietary to Fiat Chrysler Automobiles
C
11
11.5
20
Reliability
by Design
March 2014
Confidential and Proprietary to Fiat Chrysler
Automobiles
Reliability
Prediction of
Performance
Verification of
Performance
Improvement of Prediction
The best Prediction methods are quantative.
The best Verification is actual parts and systems in real usage.
The best Improvement eliminates all discrepancy between prediction and reality.
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
22
Deterministic Design
• Design parameters are deterministic, i.e., they have unique values
• CTQ’s are also deterministic, and are calculated as functions of the design
variables by transfer functions, Y = f (X1, X2, …, XN)
X1
X2
.
Design
Parameters
(X’s)
Transfer Function
Y = f (X1, X2, … XN)
XN
CTQ’s (Y’s)
Y1
.
.
.
YN
Most engineering design is deterministic
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
23
Statistical Design
• Design parameters are statistical in nature, with mean values and variation
(e.g., standard deviation)
• CTQ variations determined by statistical analysis (e.g., Monte Carlo), using the
transfer function and statistical variations in design parameters
X1
X2
.
Design
Parameters
(X’s)
Transfer Function
Y = f (X1, X2, … XN)
XN
Noise
Parameters
CTQ’s (Y’s)
Y1
.
.
.
YN
XN1 . . XNn
DFSS uses statistical design to understand and control variation
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
24
Statistical Design
Why Prototyping Doesn’t Reveal Problems
Prototyping: Single Product Copy
LSL USL
X1
X2
Xn
Selected
prototype
inputs
Y=f(X1,X2...)
Reality: Multiple Product Copies
X2
Y
Input
variability
not captured,
defects masked
LSL
X1
Xn
Range of
possible
inputs
USL
Y=f(X1,X2...)
Y
Defects
Realistic
distribution
of product
Y (CTQ)
• Prototyping does not verify product robustness
• It assesses functionality of a single, often hand-selected, sample
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
25
Statistical Design
Mechanical Example: Simply Supported Box Beam
Baseline Design
Performance Requirements:
• Applied load: 200 kg/m over 1.5 m
• Overhang = LT-L1 = 4.5 m
t
h
• Design margin must be positive,
i.e., yield strength > max stress
• 6 quality
• Low cost
WP
w
P
F
L1
LT
Analysis: Transfer function
Margin = Yield strength - Max stress
= Yield strength - (Max stress from tensile load + Max stress from bending)
Margin
March 2014
=
F
Sy - ____________
2ht + 2wt - 4t2
-
3hPWp (2LT - 2L1 - Wp)
____________________
wh3 - (w - 2t) (h - 2t)3
Confidential and Proprietary to Fiat Chrysler Automobiles
26
Statistical Design
Deterministic Design of Beam
F
Analysis: Margin = Sy - ____________ 2ht + 2wt - 4t2
Choose values for
design parameters
and applied loads:
Substituting:
3hPWp (2LT - 2L1 - Wp)
____________________
wh3 - (w - 2t) (h - 2t)3
Design Parameter/Load
Value
Beam length, LT (m)
12
7.5
Support length, L1 (m)
Beam height, h (m)
0.75
Beam width, w (m)
0.25
Section thickness, t (m)
0.05
2
89,600
Yield strength, Sy (kg/m )
Uniform load density, P (kg/m)
200
1.5
Uniform load width, Wp (m)
Tensile load, F (kg)
100
Margin = + 9,726 kg/m2
Baseline design meets positive design margin requirement,
but quality level unknown
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
27
Statistical Design
Simply Supported Box Beam
F
Analysis: Margin = Sy - ____________
2ht + 2wt - 4t2
-
3hPWp (2LT - 2L1 - Wp)
____________________
wh3 - (w - 2t) (h - 2t)3
Design parameters & applied loads are statistical in nature
• Choose mean values and a variability measure (e.g., std deviation)
• Consider tolerances
Design Parameter/Load
Mean
Beam length, LT (m)
12
Support length, L1 (m)
7.5
Beam height, h (m)
0.75
Beam width, w (m)
0.25
Section thickness, t (m)
0.05
2
Yield strength, Sy (kg/m )
89,600
Uniform load density, P (kg/m)
200
Uniform load width, Wp (m)
1.5
Tensile load, F (kg)
100
March 2014
Std Dev
Tolerances
Lower Upper
0.017
0.013
0.0033
0.0033
0.0025
3,200
3.3
0.07
1.65
0.05
0.04
0.01
0.01
0
7,500
5
0.2
5
Confidential and Proprietary to Fiat Chrysler Automobiles
0.05
0.04
0.01
0.01
0.01
0
5
0.2
5
28
Statistical Design
Simply Supported Box Beam
F
Analysis: Margin = Sy - ____________ 2ht + 2wt - 4t2
3hPWp (2LT - 2L1 - Wp)
____________________
wh3 - (w - 2t) (h - 2t)3
Do a statistical analysis (e.g., Monte Carlo), using transfer function
and statistical parameter & load values
Results:
• Margin mean
9,726 kg/m2
5,466 kg/m2
Probability
.040
Mean = 9,726
.030
.020
• Margin std dev
• Defect probability
3.8%
.010
• Design 
3.3
.000
Defects
-5,000
0
10,000
20,000
30,000
Design Margin (kg/m2)
Design margin may be positive or negative!
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
29
Statistical Design
Reaching “6”
Design optimization analysis:
• Use transfer function to understand the shape of the response surface
and the design margin’s sensitivity to each design parameter
• Reduce defects by shifting mean values or reducing variances of the
most sensitive design parameters
• Sensitivities found by partial differentiation of transfer function and
evaluation at design point
Design Parameter/Load
Mean
Std Dev
Beam length, LT (m)
12
Support length, L1 (m)
7.5
Beam height, h (m)
0.75
Beam width, w (m)
0.25
Section thickness, t (m)
0.05
2
Yield strength, Sy (kg/m )
89600
Uniform load density, P (kg/m)
200
Uniform load width, Wp (m)
1.5
Tensile load, F (kg)
100
0.017
0.013
0.0033
0.0033
0.0025
3200
3.3
0.07
1.65
March 2014
Sensitivity
- 21,003
21,003
180,205
181,676
1,158,739
1
- 393.8
- 42,007
- 11.1
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Margin most
sensitive to t,
with w and h next
30
Statistical Design
Reaching “6”
Improving the design margin:
• In general, design  can be improved by shifting means of the most
sensitive parameters or reducing their variabilities
• Although t is the most sensitive parameter, we elect to shift the mean of w
(next most sensitive) because box beams come in only a few standard
thicknesses (the next thicker beam would be too costly and heavy)
.040
Beam width, w
0.25
0.30
0.35
• Mean
9,726 17,879 24,518
• Std deviation 5,466 5,124 4,853
• Defect prob, %
3.8 0.024 0.00002
• Design 
3.3
5.0
6.5
Probability
Design margin results:
.030
.020
w = 0.25
Defects
w = 0.30
.010
w = 0.35
.000
-5,000
March 2014
0
Confidential and Proprietary to Fiat Chrysler Automobiles
10,000
20,000
30,000
Design Margin (kg/m2)
31
Problem Solving or Problem Prevention
• Discussion and Questions ??
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
32
Statistical Design
Electronics Example: Switching Power Supply
Vin = 85 - 275 Vac
Input Filter
Performance Requirements
• Output voltage, Vo: 5 V, +/-5%
• Input voltage, Vin: 85 - 275 V
• 6 quality
• Low cost
Vo = 5 Vdc, +/-5%
Isolated Switching
Converter
Feedback
V
Baseline Design
o
Isolated switching converter/
feedback section
• Baseline design combines
power MOSFET & control circuit
in a 3-pin package
•
March 2014
OPTO
•
R2
•
PWM IC
CTRL
R1
Vref
I
b
Confidential and Proprietary to Fiat Chrysler Automobiles
R1
33
Statistical Design
Deterministic Design of Power Supply
Analysis: Transfer function
Choose values for
design parameters:
Substituting:
Vo = Vref + R2
(
Vref
____ + Ib
R1
)
Design Parameter
Value
LM 431I ref voltage, Vref (volts)
R1 (ohms)
R2 (ohms)
Bias current, Ib (amps)
2.495
10,000
10,000
5.0E-06
Output voltage = 5.04 volts
Baseline design meets 5V, +/- 5% performance requirement,
but quality level unknown
March 2014
Confidential and Proprietary to Fiat Chrysler Automobiles
34
Statistical Design
Switching Power Supply
Transfer function
(unchanged)
• Design parameters are
statistical in nature. Choose
mean values and a variability
measure (e.g., std deviation):
• Do a statistical analysis
(e.g., Monte Carlo), using the
transfer function and the
statistical parameter values
Results:
• Vo mean
5.04 volts
0.059 volts
• Vo std dev
• Defects/million 188 (5.06)
March 2014
(
Vo = Vref + R2
Design Parameter
Vref
____ + Ib
R1
Mean Std Dev
)
Tolerances
Lower
Upper
LM 431I Vref (volts)
2.495 0.0283
0.085
0.085
R1 (ohms)
10,000
33.33
1%
1%
10,000
33.33
1%
1%
R2 (ohms)
Bias current, Ib (amps) 5.0E-06 1.15E-06 2.00E-06 2.00E-06
.035
Probability
Analysis:
.026
.017
.009
.000
4.75
4.875
5.00
Volts
5.125
Baseline design meets 5V, +/- 5% performance
requirement, but quality level is not 6
Confidential and Proprietary to Fiat Chrysler Automobiles
5.25
35
Statistical Design
Reaching “6”
Design optimization analysis:
• Use transfer function to understand the shape of the response surface
and the output voltage’s sensitivity to each design parameter
• Reduce defect rate by shifting mean values or reducing variances of
design parameters
Design Parameter
LM 431I Vref (volts)
R1 (ohms)
R2 (ohms)
Bias current, Ib (amps)
Mean
2.495
10,000
10,000
5.0E-06
March 2014
Centered
.038
Probability
• Vo std dev
• Defects/million
5.00 volts
0.058 volts
20 (5.61)
Sensitivity
2
-0.0002495
0.0002545
10,000
Base
Design Mod 1: Center distribution
by increasing R1 to 10,160 ohms
Results:
• Vo mean
Std Dev
0.0283
33.33
33.33
1.15E-06
.028
.019
.009
.000
4.75
Confidential and Proprietary to Fiat Chrysler Automobiles
4.875
5.00
Volts
5.125
5.25
36
Statistical Design
Reaching “6” (cont’d)
Design Mod 2: Mod 1 plus 0.1%
resistors to reduce resistor variance
Centered
Design Mod 3: Mod 2 plus LM 431AI
MOSFET to reduce Vref variance
Base
0.1% Resistors
MOSFET Upgrade
0.1% Resistors
.050
Probability
Probability
.038
.028
.019
.009
.000
4.75
Summary
March 2014
4.875
5.00
Volts
5.125
5.25
Mean
.037
.025
.012
.000
4.75
Std Dev DPMO
4.875
5.00
Volts
Z ST
Cost
Baseline Design
Mod 1: Centered via R 1
5.04
5.00
0.059
0.058
189
20
5.06
5.61
100%
100%
Mod 2: 0.1% Resistors
Mod 3: LM 431AI
5.00
5.00
0.057
0.041
13
~0
5.7
7.58
101%
105%
Statistical design enables performance, quality
& cost prediction during the design process
Confidential and Proprietary to Fiat Chrysler Automobiles
5.125
5.25
37
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