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Case Study - SMC Consistency:
A Data-Based Technique to Quality
Improvement
Probir Guha
Larry Baer
Mike Siwajek
Michael Hiltunen
Objective
Improve product quality at molding plant
Improve FTY
Use actual production quality data to make
improvements
Improvements based on using the SMC
Consistency Technique
Focus on improvements through SMC material
improvements
2
Pickup Box Molding
3
SMC Consistency
SMC Consistency requires
Production data on
• Raw material
– Acid Number
– Molecular Weight
– Viscosity
– Cure time
– Etc.
• Process inputs
– Mold temperature
– Mold Close Rate
– Max vacuum
– Etc.
Product data
• Defect rate
• Dimension
• Strength
• Etc.
Utilizes actual production information
for improvements
SMC Consistency utilizes actual
production data to identify key factors
affecting desired outcome
The process requires a sound data
gathering system in place
DOE’s require special runs and forced
variations to actual process and raw
material
SMC Consistency does not replace
DOE’s
For us SMC Consistency is an
additional tool
4
SMC Consistency
FTY Data @ molding Plant
Regress versus SMC Cert package
Identify top 3 SMC characteristics affecting negative outcome
Regress each characteristic versus SMC Raw material characteristics
Identify up to top 9 characteristics that affects outcome
Brainstorm plausible failure mechanism for each characteristic identified
Select characteristics with plausible failure modes for follow-up action
Follow-up actions Review data variability
Discuss improvements required with supplier
Implement change
Continue to monitor FTY data
5
Product Characteristic vs.
Time
Corresponding SMC
Characteristics
Regress Product Criteria vs.
SMC Properties
Identify Top 3 SMC Properties
Affecting Outcome - A, B, C
Regress SMC Property B vs.
Raw Material Characteristics
Identify Top 3 Raw Materials
Affecting B
Brainstorm Failure Modes
Select Characteristic w/
Assignable Failure Mode for
Action
Study Variability
Continue to Monitor Product
Characteristic
Regress SMC Property A vs.
Raw Material Characteristics
Regress SMC Property C vs.
Raw Material Characteristics
Identify Top 3 Raw Materials
Affecting A
Identify Top 3 Raw Materials
Affecting C
Activity Away from Plants
Activity Primarily at
Compounding Plant
Activity Primarily at Molding
Plant
6
Normalized FTY
FTY data has been normalized to code actual data
Normalization between 100% FTY and minimum FTY
Data spread over an approximately 180 day
production period
Normalized FTY = Actual Daily FTY - Minimum FTY
100% - Minimum FTY
7
Normalized FTY
(Moving Average)
8
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0 10 20 30 40 50 60
No
rma
lize
d F
TY
Days of Production
Observations
2 month data summary showed a 5X swing in
normalized defect rate
No obvious root causes
Traditional root causes were discussed
Seasonal
Formulation and/or Raw Material changes – none made
Deterioration in fiber wet-out – no obvious deterioration
SMC machine compaction system maintenance – no effect
etc
Loss in FTY continued9
SMC Compounding Plant
SMC is manufactured at CSP’s Van Wert, OH factory
VW certifies certain properties for each batch of
material manufactured
SMC Properties certified relate to:
Viscosity build
Glass content
Product weight or areal density
Product density
SMC cure characteristics
10
Typical SMC Certificate
11
Molding Plant Defect vs.
SMC Cert Data
Summary
Molding plant records daily defect data
% defect by day/shift of production
Identifies SMC Batch#
Defect rate regressed versus SMC batch-wise Cert Data
A-side viscosity added to matrix
Cert data includes
Product Weight
Glass Content
Cure & Gel
Shrinkage
Density
13
Regression : Defect Rate
vs. SMC Cert Data• 432 data sets covering a 5 month
production period
• 67 predictors from incoming raw
material quality data
• Stepwise regression identified 3
properties
Factors that affected the outcome
(defect rate)
p-value of 0.000 indicated the
factors were found to be
statistically significant with a
high confidence level
R-sq value of 65.94% indicated a
high amount of the outcome
variability attributed to the 3
factors identified
The 3 key factors
Gel Time
A-side Viscosity
Final Cure Time
14
Step 1 2 3 4 5 6
Constant -3.6683 -5.2329 -1.3675 -1.6864 -0.1478 -0.2216
Gel Time 0.1308 0.1433 0.1275 0.1225 0.118 0.1157
T-Value 11.24 14.06 15.04 14.8 13.91 13.51
P-Value 0 0 0 0 0 0
A-side Viscosity 0.0004 0.00043 0.00045 0.00044 0.00044
T-Value 9.24 12.09 12.93 12.96 13
P-Value 0 0 0 0 0
Final Cure -0.0453 -0.0607 -0.0584 -0.0579
T-Value -11.25 -11.53 -10.93 -10.86
P-Value 0 0 0 0
80% Cure 0.0337 0.0328 0.0316
T-Value 4.35 4.26 4.11
P-Value 0 0 0
Density -0.92 -0.82
T-Value -2.13 -1.89
P-Value 0.034 0.06
Shrinkage 1.13
T-Value 1.67
P-Value 0.095
S 0.237 0.206 0.169 0.163 0.162 0.162
R-Sq 32.87 49.59 66.27 68.6 69.16 69.49
R-Sq(adj) 32.73 49.17 65.94 68.11 68.55 68.77
Response is normalized on 10 predictors with N=260
Normalized FTY vs.
SMC Gel TimeD
esir
able
Desirable
15
0
0.2
0.4
0.6
0.8
1
28 29 30 31 32 33 34 35 36 37
No
rma
lize
d F
TY
SMC Gel Time
Analysis of Variance
Source DF SS MS F P
Regression 1 7.1500 7.14999 126.767 0.000
Error 259 14.6082 0.05640
Total 260 21.7582
Normalized FTY vs.
A-side ViscosityD
esir
able
Desirable16
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2000 2500 3000 3500 4000 4500
No
rma
lize
d F
TY
A-side Viscosity (cps)
Analysis of Variance
Source DF SS MS F P
Regression 1 2.3597 2.35967 31.5052 0.000
Error 259 19.3986 0.07490
Total 260 21.7582
Normalized FTY vs.
Final Cure TimeD
esir
able
Desirable17
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
68 70 72 74 76 78 80 82
No
rma
lize
d F
TY
SMC Final Cure Time (seconds)
Analysis of Variance
Source DF SS MS F P
Regression 1 4.8502 4.85019 74.2959 0.000
Error 256 16.9080 0.06528
Total 260 21.7582
Key SMC Factors vs. Raw
Material Data
Summary
In this phase, the 3 key SMC Cert Properties were analyzed versus all SMC
raw material properties
Over 50 raw Material Properties were included in the matrix
Several months of Raw Material properties were regressed versus the 3
key SMC Cert Properties
In excess of 25,000 data points used in the analysis
Raw Material Properties included: Resin – MW; Viscosity; Solids; Acid Number; moisture; cure; etc
LPA - MW; Viscosity; Solids; Acid Number; moisture; etc
Catalyst – Purity; Active Oxygen; cure; etc
Additives – minor ingredients; viscosity; etc
Release – MP; Fatty Acid; Moisture; Particle Size; etc
Filler – Particle Size; Moisture; etc
Thickener – Viscosity; Active Ingredient; Moisture; etc
19
SMC Gel Time vs. Raw Material
Data
SMC Gel Time vs. SMC
Raw Material• 432 data sets covering a 5 month
production period
• 67 predictors from incoming raw
material quality data
• Stepwise regression identified 3
properties
– Factors that affected the outcome
(SMC Gel Time)
– p-value of 0.000 indicated the
factors were found to be statistically
significant with a high confidence
level
– R-sq value of 56.74% indicated a
high amount of the outcome
variability attributed to the 3 factors
identified
• The 3 key factors
– Catalyst Peak Temperature
– LPA Molecular Weight
– LPA Acid Number
21
Step 1 2 3 4 5 6 7
Constant 70.11 74.07 74.65 74.04 82.57 82.88 80.82
Catalyst Peak Temp -0.0978 -0.1103 -0.1089 -0.1072 -0.1085 -0.1057 -0.0994
T-Value -19.8 -22.13 -22.71 -22.76 -23.31 -22.64 -19.74
P-Value 0 0 0 0 0 0 0
LPA Molecular Weight 0.00003 0.00004 0.00004 0.00004 0.00004 0.00004
T-Value 7.19 8.35 9.01 9.64 9.24 8.57
P-Value 0 0 0 0 0 0
LPA Acid Number -0.45 -0.548 -0.538 -0.579 -0.561
T-Value -6.09 -7.24 -7.22 -7.77 -7.59
P-Value 0 0 0 0 0
LPA Water Content 5.3 5.7 6.3 6.7
T-Value 4.43 4.81 5.39 5.69
P-Value 0 0 0 0
Thickener Density -5.2 -5.4 -5.4
T-Value -3.67 -3.83 -3.88
P-Value 0 0 0
Thickener 48 Hr -1.16 -1.14
T-Value -3.5 -3.44
P-Value 0.001 0.001
Filler Acid Soluble -0.86
T-Value -3.14
P-Value 0.002
S 0.532 0.503 0.483 0.473 0.466 0.46 0.455
R-Sq 47.7 53.32 57.05 58.93 60.19 61.31 62.18
R-Sq(adj) 47.58 53.1 56.74 58.55 59.73 60.76 61.56
Response is SMC Gel Time on 67 Predictors with N = 432
SMC Gel Time vs.
Catalyst Peak TempD
esir
able
Desirable 22
28
29
30
31
32
33
34
35
36
37
385 390 395 400 405 410 415
SM
C G
el T
ime
(sec
on
ds)
Catalyst Peak Temperature ( F)
Analysis of Variance
Source DF SS MS F P
Regression 1 110.899 110.899 392.201 0.000
Error 430 121.587 0.283
Total 431 232.487
SMC Gel Time vs.
LPA Molecular Weight
23
Des
irab
le
28
29
30
31
32
33
34
35
36
37
25000 30000 35000 40000 45000 50000
SM
C G
el T
ime
(sec
on
ds)
LPA Molecular Weight
Analysis of Variance
Source DF SS MS F P
Regression 1 0.089 0.089211 0.165066 0.685
Error 430 232.397 0.540459
Total 431 232.487
SMC Gel Time vs.
LPA Acid Number
24
Des
irab
le
28
29
30
31
32
33
34
35
36
37
2 2.5 3 3.5
SM
C G
el T
ime
(sec
on
ds)
LPA Acid Number
Analysis of Variance
Source DF SS MS F P
Regression 1 12.113 12.1126 23.6345 0.000
Error 430 220.374 0.5125
Total 431 232.487
SMC A-side Viscosity vs.
Raw Material Data
SMC A-side Viscosity
vs. Raw Material• 432 data sets covering a 5
month production period
• 67 predictors from incoming
raw material quality data
• Stepwise regression
identified 3 properties
– Factors that affected the
outcome (SMC Gel Time)
– p-value of 0.000 indicated the
factors were found to be
statistically significant with a
high confidence level
– R-sq value of 21.17% indicated
a moderate amount of the
outcome variability attributed
to the 3 factors identified
• The 3 key factors
– VE Acid Number
– Filler Fines Content
– VE Gel Time
26
Step 1 2 3 4 5 6 7
Constant -2150 -3322 -1416 3179 -23144 -19840 -14603
VE Acid Number 130 119 93 71 61 44 35
T-Value 9.36 8.8 6.8 5.14 4.54 3.35 2.75
P-Value 0 0 0 0 0 0.001 0.006
Filler Fines 62 72.1 73.7 62.5 75 75.3
T-Value 6.6 7.84 8.21 7.07 8.56 8.89
P-Value 0 0 0 0 0 0
VE Gel Time -263 -308 -368 -354 -401
T-Value -7.11 -8.36 -10.03 -9.92 -11.41
P-Value 0 0 0 0 0
VE Peak
Temperature-9 -10.1 -12.7 -14.3
T-Value -6.19 -7.11 -8.93 -10.22
P-Value 0 0 0 0
LPA Solids 433 562 511
T-Value 6.9 8.83 8.23
P-Value 0 0 0
VE Solids -163 -200
T-Value -6.93 -8.52
P-Value 0 0
MgO Content 35.8
T-Value 7.02
P-Value 0
S 269 261 253 246 239 231 224
R-Sq 10.85 15.96 21.5 25.48 30.13 34.53 38.76
R-Sq(adj) 10.73 15.72 21.17 25.06 29.64 33.98 38.16
Response is A-side Viscosity on 67 Predictors with N = 432
SMC A-side Viscosity
vs. VE Acid NumberD
esir
able
Desirable 27
2000
2200
2400
2600
2800
3000
3200
3400
3600
3800
4000
38 39 40 41
SM
C A
-sid
e V
isco
sity
(cp
s)
VE Acid Number
Analysis of Variance
Source DF SS MS F P
Regression 1 6326129 6326129 87.5365 0.000
Error 719 51961045 72268
Total 720 58287174
SMC A-side Viscosity vs.
Filler Fines ContentD
esir
able
Desirable 28
2000
3000
4000
24 24.5 25 25.5 26 26.5 27 27.5 28 28.5 29
A-s
ide
Vis
cosi
ty (
cps)
Filler Fines Content
Analysis of Variance
Source DF SS MS F P
Regression 1 4021220 4021220 53.2794 0.000
Error 719 54265954 75474
Total 720 58287174
SMC A-side Viscosity
vs. VE Gel TimeD
esir
able
Desirable 29
2000
2200
2400
2600
2800
3000
3200
3400
3600
3800
4000
3.8 4 4.2 4.4 4.6 4.8
A-s
ide
Vis
cosi
ty (
cps)
VE Gel Time (CP2)
Analysis of Variance
Source DF SS MS F P
Regression 1 4422860 4422860 59.0379 0.000
Error 719 53864315 74916
Total 720 58287174
SMC Final Cure Time vs.
Raw Material Data
SMC Final Cure vs.
Raw Material
• 432 data sets covering a 5
month production period
• 67 predictors from incoming
raw material quality data
• Stepwise regression identified
3 properties
– Factors that affected the outcome
(SMC Final Cure)
– p-value of 0.000 indicated the
factors were found to be
statistically significant with a high
confidence level
– R-sq value of 23.18% indicated a
moderate amount of the outcome
variability attributed to the 3
factors identified
• The 3 key factors
– Catalyst Peak Temperature
– VE Viscosity
– Filler Acid Solubles
31
Step 1 2 3 4 5 6 7
Constant 11.001 2.997 14.611 19.95 85.694 100.103 93.943
Catalyst Peak Temp 0.161 0.156 0.116 0.113 0.094 0.047 0.029
T-Value 8.07 8.06 5.74 5.69 4.62 1.88 1.16
P-Value 0 0 0 0 0 0.061 0.246
VE Viscosity 0.0097 0.0108 0.0082 0.0108 0.0102 0.0073
T-Value 5.31 6.06 4.41 5.38 5.15 3.4
P-Value 0 0 0 0 0 0.001
Filler Acid Soluble 6.4 7.4 7.6 8.7 9.3
T-Value 5.41 6.19 6.45 7.14 7.62
P-Value 0 0 0 0 0
Thickener Moisture -7.4 -7.7 -7.9 -8.6
T-Value -3.93 -4.14 -4.27 -4.67
P-Value 0 0 0 0
VE Solids -1 -0.96 -0.99
T-Value -3.31 -3.19 -3.33
P-Value 0.001 0.002 0.001
VE Moisture 53 65
T-Value 3.17 3.87
P-Value 0.002 0
VE Acid Number 0.46
T-Value 3.27
P-Value 0.001
S 2.14 2.08 2.01 1.98 1.96 1.94 1.92
R-Sq 13.16 18.51 23.72 26.38 28.22 29.88 31.61
R-Sq (adj.) 12.96 18.13 23.18 25.69 27.38 28.89 30.48
Response is Final Cure Time on 67 Predictors with N = 432
SMC Final Cure vs.
Catalyst Peak TempD
esir
able
Desirable32
70
71
72
73
74
75
76
77
78
79
80
385 390 395 400 405 410 415 420
SM
C F
ina
l Cu
re (se
con
ds)
Catalyst Peak Temperature ( F)
Analysis of Variance
Source DF SS MS F P
Regression 1 299.27 299.270 65.1800 0.000
Error 430 1974.32 4.591
Total 431 2273.69
SMC Final Cure vs.
VE ViscosityD
esir
able
Desirable33
70
75
80
900 1000 1100
SM
C F
ina
l Cu
re (se
con
ds)
VE Viscosity (cps)
Analysis of Variance
Source DF SS MS F P
Regression 1 140.11 140.106 28.2382 0.000
Error 430 2133.48 4.962
Total 431 2273.59
SMC Final Cure vs.
Filler Acid SolubleD
esir
able
Desirable34
70
75
80
0.3 0.4 0.5 0.6 0.7 0.8
SM
C F
ina
l Cu
re (se
con
ds)
Filler Acid Soluble
Analysis of Variances
Source DF SS MS F P
Regression 1 230.21 230.213 48.4452 0.000
Error 430 2043.38 4 .752
Total 431 2273.59
Brainstorm Failure Mode
Failure Modes Discussion
36
SMC Cert Property Raw Material Characteristic Priority Failure Mode
Catalyst Peak Temperature High High Heat Exotherm
LPA Molecular Weight Low Very weak effect - Dropped
LPA Acid Number Low Very weak effect - Dropped
VE Acid Number Medium Increased hydrogen bonding improves glass carrying capability
Filler Fines Content Medium Improves fiber carrying capability at mold temperature
VE Gel Time Low Mechanism not clear - Dropped
Catalyst Peak Temperature High High Heat Exotherm - most important factor
VE Viscosity Low Failure mode not fully understood - Dropped
Filler Acid Solubles Low Failure mode not fully understood - Dropped
SMC Gel Time
SMC A-side Viscosity
SMC Final Cure
SMC/Raw Material Improvements
Factor 1: Catalyst
Peak Temperature
• Over the period of the SMC Consistency Study we were able to drive the
Catalyst Peak temperature down
• This was the most significant factor that was contributing to the defect38
385
390
395
400
405
410
415
420
0 100 200 300 400 500 600 700 800
Ca
taly
st 1
Pea
k T
emp
era
ture
Time
Catalyst Peak Temperature vs. Time
Factor 2:
VE Acid Number
• Over the period of the SMC Consistency Study we were able to drive the VE
Acid Number upward
• This was the second most significant factor that was contributing to the defect39
37
38
39
40
41
42
0 100 200 300 400 500 600 700 800
VE
Aci
d N
um
ber
Time
VE Acid Number vs. Time
Factor 3:
Filler Fines Fraction
• Over the period of the SMC Consistency Study we were unable to shift
the Filler Fines Fraction upwards
• This may require working closer with the supplier to fine tune their
process to get the desired outcome40
23
24
25
26
27
28
0 100 200 300 400 500 600 700 800
Fil
ler
Fin
es F
ract
ion
Time
Filler Fines Fraction vs. Time
Results
Improvement in Normalized
FTY (moving average)
42
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0 20 40 60 80 100 120 140 160 180 200
No
rma
lize
d F
TY
Days of Production
The SMC Consistency technique allowed us to focus
on 3 factors out of 67
We were able to use daily production generated data
to improve product quality
The technique requires a strong commitment on the
respective plants to generate data
We had excellent data collection both at our molding plant
and the compounding plant
We are now utilizing the technique for improvements
in other SMC formulations
Summary
43
The Next SMC
Consistency Project!
44
Step 1 2 3 4 5 6 7
Constant 864.4 925.3 891.8 854.7 967.6 762.2 1030.9
9 -8.44 -8.6 -8.14 -8.07 -9.15 -7.02 -7
T-Value -14.9 -16.42 -15.95 -16.21 -14.99 -8.4 -8.59
P-Value 0 0 0 0 0 0 0
35 -0.217 -0.261 -0.208 -0.26 -0.277 -0.282
T-Value -5.99 -7.25 -5.42 -6.26 -6.81 -7.12
P-Value 0 0 0 0 0 0
33 -100 -96 -101 -87 -82
T-Value -4.5 -4.45 -4.73 -4.15 -3.97
P-Value 0 0 0 0 0
43 7.5 7.7 7.7 9.1
T-Value 3.41 3.57 3.7 4.37
P-Value 0.001 0 0 0
14 0.48 0.65 0.75
T-Value 2.95 3.97 4.62
P-Value 0.004 0 0
18 -0.324 -0.316
T-Value -3.6 -3.6
P-Value 0 0
42 -7.5
T-Value -3.39
P-Value 0.001
S 3.93 3.62 3.46 3.37 3.31 3.21 3.13
R-Sq 52.47 59.69 63.41 65.44 66.91 68.96 70.68
R-Sq(adj) 52.24 59.29 62.86 64.74 66.07 68.01 69.63
Response is Day-3 Viscosity on 53 Predictors with N = 203
Thank you
