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Questions and Answers
How Relevant Questions
Obtain
Useful Answers
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 1
Judson B. EstesFiat Chrysler Automobiles
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 2
Weave the wisdom from many available tool sets into a package of training, certification and project work1. 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. ContrastA Measurable difference in performance.How do you measure the performance?How Big is the difference?
3. ConvergeUse Logical Strategies to isolate the candidate cause.What split are you making?How does that narrow the possible causes?
4. ConfirmTest the candidate cause to prove it is the true root cause.What is your Statistical Confidence?When can we implement the fix?
Focus on the 4 C’s
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 3
Collect Phase
• Describe Problem
• Identify Possible Causes
• Evaluate Possible Measurements
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 4
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 5
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
IS IS NOTDescribe the problem in
detail.
Tighten IS data. Help eliminate
possible causes.
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 6
Other potential lab conclusions could have been but were not "cold shock", "high voltage" & "wear out"
LOP 085032 Needs replacement Some examined from Field, Hot shock is the main conclusion from the Sylvania lab report
2. Defect
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.
low beam bulb # L0009006 used in LX 300 models LXCH48, LXCP48, LXFP48 . Click here to see VIN list
1. ObjectWHAT:
(IS NOT observed/reported)(IS observed / reported)factsNON-PROBLEM AREAPROBLEM ARPEADescription
LX low beam bulb infant failure Problem Statement:
[1] PROBLEM AREA
PROBLEM SOLVING
Collect Phase Example
“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 KelvinMarch 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 7
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 8
Contrast Phase
0 1 4Length (mm)
CurrentRequired
Freq
uenc
y
0-3 3Flushness (mm)
Current
Required
Freq
uenc
y
-1.5 1.5
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 9
Contrast Phase
Cloth seats
Seat back
Seam A
BOB/WOW seamWOW cushion
Otherstrategies
Seam B
Seat cushion
Driver side Passenger side
Front seat Rear seat
Leather seats
Open seams on DRseats resulting in high
warranty costs
0 1 4Width (mm)
CurrentRequired
Freq
uenc
y
Problem Definition Statement
90% of returns are leather
83% of returns are front seats
71% of returns are driver side seats
92% of returns and narratives are seat cushions
Examination of returned product showsseam B accounts for 42 out of 54 claims
See Strategy Diagram
Find and eliminate the Red Xcausing open seams on the DRfront driver side leather seats
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 10
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 11
Measure twice and get the same answer
on BOB and WOW
Contrast Phase example
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 12
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 13
5 Whys to the Root Cause
Ishikawa Fishbone Diagram
IS/ IS Not Problem Specifications
Shainin Red X Strategies
Classical and Taguchi
Design of Experiments
Six Sigma
Pure Statistics
TRIZ and Systemology
Reactive Problem Solving Hierarchy
Innovation and Evolution
No Strategy and All Tools
Simple Strategy and Most Tools
Multiple Variables and Interactions
Multiple Strategies, Easy Statistics
Distinctions and Changes
Organized Brainstorming
Simple Questioning
Use the Right Tool for the Problem
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 14
5 Whys to the Root Cause
Ishikawa Fishbone Diagrams
Critical Thinking
Shainin
Classical and Taguchi
Design of Experiments
Six Sigma
Pure Statistics
TRIZ and Systemology
Problem Solving Hierarchy
Easiest to Grasp
Hardest to Grasp
Most Widely Used
Least Widely Used
More Variables and Interactions
Increased Variation and Environment
Changes
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 15
1 2 3 4 5 6 7 8ABCDEF
x
xxxxxxxxxx
xx
xx xx
xxxxxxx
Concentration Diagram example
Paint Craters on “B” pillar
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 16
Component Search Stage 2
• Plotting0
1020
30
Gre
en Y
= lb
s.
Orig. 1st D/R 2nd D/R 3rd D/R S1 orig
* * * *
+ + + +
WOW
BOB
.Stage 1
*
+
+
*
Stage 2
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 17
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 18
Six Pack B vs. C
• B
B is the “Better” part or process or sub-assembly or material
• C
C is the “Current” part or process or sub-assembly or material
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 19
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.
Run Order B or C Diameter (mm)
1 C 10.6
2 B 8.3
3 C 11.2
4 C 9.8
5 B 9.1
6 B 8.8
B 8.3
B 8.8
B 9.1
C 9.8
C 10.6
C 11.2
Rank Order
The end count equals 6. Therefore, it can be stated with 95% confidence that the B’s are better than the C’s.
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 20
Six Pack B vs. C Test Example
• Distribution of two groups looks something like this.
8.0 8.5 9.0 9.5 10 10.5 11 11.5
B B B C C C
March 2014Confidential and Proprietary to Fiat Chrysler
Automobiles
Reliability by Design
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 22
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.
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)
DesignParameters
(X’s)CTQ’s (Y’s)
Y1...
YN
Transfer FunctionY = f (X1, X2, … XN)
Most engineering design is deterministic
X1
X2
.XN
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
DesignParameters
(X’s)X1
X2
.XN
Noise Parameters XN1 . . XNn
CTQ’s (Y’s)
Y1...
YN
Transfer FunctionY = f (X1, X2, … XN)
DFSS uses statistical design to understand and control variationMarch 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 24
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 25
Statistical DesignWhy Prototyping Doesn’t Reveal Problems
• Prototyping does not verify product robustness• It assesses functionality of a single, often hand-selected, sample
Reality: Multiple Product CopiesPrototyping: Single Product Copy
Range of possible inputs
USLLSLX1
X2Y=f(X1,X2...)
YXnInput
variabilitynot captured,
defects masked
Selectedprototype
inputs
USLLSL
Y
Realisticdistributionof product
Y (CTQ)
Defects
X1
X2
Xn
Y=f(X1,X2...)
Statistical DesignMechanical Example: Simply Supported Box Beam
P
L1
LT
WP
F
th
w
Performance Requirements:• Applied load: 200 kg/m over 1.5 m• Overhang = LT-L1 = 4.5 m• Design margin must be positive,
i.e., yield strength > max stress• 6 quality• Low cost
Performance Requirements:• Applied load: 200 kg/m over 1.5 m• Overhang = LT-L1 = 4.5 m• Design margin must be positive,
i.e., yield strength > max stress• 6 quality• Low cost
Analysis: Transfer functionMargin = Yield strength - Max stress
= Yield strength - (Max stress from tensile load + Max stress from bending)
F 3hPWp (2LT - 2L1 - Wp)Margin = Sy - ____________ - ____________________
2ht + 2wt - 4t2 wh3 - (w - 2t) (h - 2t)3
Baseline Design
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 26
Statistical DesignDeterministic Design of Beam
F 3hPWp (2LT - 2L1 - Wp)Analysis: Margin = Sy - ____________ - ____________________ 2ht + 2wt - 4t2 wh3 - (w - 2t) (h - 2t)3
Choose values for design parameters and applied loads:
Substituting: Margin = + 9,726 kg/m2
Design Parameter/Load ValueBeam length, LT (m) 12Support length, L1 (m) 7.5Beam height, h (m) 0.75Beam width, w (m) 0.25Section thickness, t (m) 0.05Yield strength, Sy (kg/m2) 89,600Uniform load density, P (kg/m) 200Uniform load width, Wp (m) 1.5Tensile load, F (kg) 100
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 27
Baseline design meets positive design margin requirement,but quality level unknown
Statistical DesignSimply Supported Box Beam
Design Parameter/Load Mean Std Dev TolerancesLower Upper
Beam length, LT (m) 12 0.017 0.05 0.05Support length, L1 (m) 7.5 0.013 0.04 0.04Beam height, h (m) 0.75 0.0033 0.01 0.01Beam width, w (m) 0.25 0.0033 0.01 0.01Section thickness, t (m) 0.05 0.0025 0 0.01Yield strength, Sy (kg/m2) 89,600 3,200 7,500 0Uniform load density, P (kg/m) 200 3.3 5 5Uniform load width, Wp (m) 1.5 0.07 0.2 0.2Tensile load, F (kg) 100 1.65 5 5
Design parameters & applied loads are statistical in nature • Choose mean values and a variability measure (e.g., std deviation) • Consider tolerances
F 3hPWp (2LT - 2L1 - Wp)Analysis: Margin = Sy - ____________ - ____________________ 2ht + 2wt - 4t2 wh3 - (w - 2t) (h - 2t)3
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 28
Statistical DesignSimply Supported Box Beam
Design margin may be positive or negative!
Do a statistical analysis (e.g., Monte Carlo), using transfer function and statistical parameter & load values
Results:• Margin mean 9,726 kg/m2
• Margin std dev 5,466 kg/m2
• Defect probability 3.8% • Design 3.3
F 3hPWp (2LT - 2L1 - Wp)Analysis: Margin = Sy - ____________ - ____________________ 2ht + 2wt - 4t2 wh3 - (w - 2t) (h - 2t)3
.000
.010
.020
.030
.040
-5,000 10,000 20,000 30,0000
Prob
abili
ty
Design Margin (kg/m2)
Mean = 9,726
Defects
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 29
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
Statistical DesignReaching “6”
Design Parameter/Load Mean Std Dev Sensitivity
Beam length, LT (m) 12 0.017 - 21,003Support length, L1 (m) 7.5 0.013 21,003Beam height, h (m) 0.75 0.0033 180,205Beam width, w (m) 0.25 0.0033 181,676Section thickness, t (m) 0.05 0.0025 1,158,739Yield strength, Sy (kg/m2) 89600 3200 1Uniform load density, P (kg/m) 200 3.3 - 393.8Uniform load width, Wp (m) 1.5 0.07 - 42,007Tensile load, F (kg) 100 1.65 - 11.1
Margin most sensitive to t,
with w and h next
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 30
Design margin results: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
Statistical DesignReaching “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)
.000
.010
.020
.030
.040
-5,000 10,000 20,000 30,0000
Prob
abili
ty
Design Margin (kg/m2)
w = 0.25
w = 0.30
w = 0.35
Defects
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 31
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 32
Problem Solving or Problem Prevention
• Discussion and Questions ??
Statistical DesignElectronics Example: Switching Power Supply
Baseline Design• Isolated switching converter/ feedback section
• Baseline design combines power MOSFET & control circuit in a 3-pin package
Input Filter Isolated Switching Converter
Feedback
Vo = 5 Vdc, +/-5%Vin = 85 - 275 Vac
Performance Requirements• Output voltage, Vo: 5 V, +/-5% • Input voltage, Vin: 85 - 275 V• 6 quality• Low cost
R2
R1CTRL
Vo
PWM IC
OPTO
VrefIb
••
R1
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 33
Statistical DesignDeterministic Design of Power Supply
Baseline design meets 5V, +/- 5% performance requirement,but quality level unknown
Analysis: Transfer function
Choose values for design parameters:
Substituting: Output voltage = 5.04 volts
Design Parameter ValueLM 431I ref voltage, Vref (volts) 2.495 R1 (ohms) 10,000R2 (ohms) 10,000Bias current, Ib (amps) 5.0E-06
VrefVo = Vref + R2 ____ + Ib
R1
( )
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 34
Statistical DesignSwitching Power Supply
Design Parameter Mean Std Dev TolerancesLower
UpperLM 431I Vref (volts) 2.495 0.0283 0.085 0.085R1 (ohms) 10,000 33.33 1% 1%R2 (ohms) 10,000 33.33 1% 1%Bias current, Ib (amps) 5.0E-06 1.15E-06 2.00E-06 2.00E-06
Analysis: Transfer function(unchanged)
• Design parameters are statistical in nature. Choose mean values and a variabilitymeasure (e.g., std deviation):
Baseline design meets 5V, +/- 5% performance requirement, but quality level is not 6
• Do a statistical analysis(e.g., Monte Carlo), using the transfer function and the statistical parameter values
Results:• Vo mean 5.04 volts• Vo std dev 0.059 volts• Defects/million 188 (5.06)
Vref Vo = Vref + R2 ____ + Ib
R1
( )
4.75 4.875 5.00 5.125 5.25Volts
.000
.009
.017
.026
.035Pr
obab
ility
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 35
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
Statistical DesignReaching “6”
Design Parameter Mean Std Dev SensitivityLM 431I Vref (volts) 2.495 0.0283 2R1 (ohms) 10,000 33.33 -0.0002495R2 (ohms) 10,000 33.33 0.0002545Bias current, Ib (amps) 5.0E-06 1.15E-06 10,000
Design Mod 1: Center distribution by increasing R1 to 10,160 ohms
Results:• Vo mean 5.00 volts• Vo std dev 0.058 volts• Defects/million 20 (5.61)
4.75 4.875 5.00 5.125 5.25Volts
Prob
abili
tyBase Centered
.000
.009
.019
.028
.038
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 36
Statistical Design Reaching “6” (cont’d)
Summary
Statistical design enables performance, quality & cost prediction during the design process
Design Mod 3: Mod 2 plus LM 431AI MOSFET to reduce Vref variance
Base 0.1% ResistorsMOSFET Upgrade
.000
.012
.025
.037
.050
4.75 4.875 5.00 5.125 5.25Volts
Prob
abili
ty
Design Mod 2: Mod 1 plus 0.1% resistors to reduce resistor variance
Centered 0.1% Resistors
.000
.009
.019
.028
.038
4.75 4.875 5.00 5.125 5.25Volts
Prob
abili
ty
Mean Std Dev DPMO ZST CostBaseline Design 5.04 0.059 189 5.06 100%
Mod 1: Centered via R1 5.00 0.058 20 5.61 100%Mod 2: 0.1% Resistors 5.00 0.057 13 5.7 101%Mod 3: LM 431AI 5.00 0.041 ~0 7.58 105%
March 2014 Confidential and Proprietary to Fiat Chrysler Automobiles 37