VIETNAM PLANT
FINAL REPORT
Active-Activa One Piece
Fire Loss Reduction
BB Project #AP 2165
1
Asia Pacific
B. Executive Summary
1. Problem Description
 Baseline statistics of production loss:
•
•
•
•
FF Loss: 26.7% (Y1)
RF Loss: 29.1% (y2)
TTL: 45.3% (y)
Major defects includes 70.5% over total FF defects:
-Clay crack (CC)- loss of total FF pcs (y)
-CDT & PHT loss of RF loss …
* Shortage Supply vs Demand 15.7% volume around 200 A
pcs/month
 Project targets
 FF loss : 18 %
 RF loss : 21%
 TT loss : 29.9
2
Asia Pacific
Baseline study - FFL and RFL& Shortage Demand in 2009
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Trend of RFL
Trend of FFL
100
50
80
40
60
%
%
30
20
40
10
20
0
Jan
Feb
Mar
May
Jun
Jul
Aug
Sep
Oct
Nov
0
Dec
Jan
BSL FFL
Target FFL
FF Loss%
Feb
Mar
May
BSL RFL
Jun
Jul
Target RFL
Aug
Sep
Oct
Nov
Dec
RF Loss %
Trend of TTL
80
%
60
40
20
0
Jan
Feb
Mar
May
Target TTL
3
Jun
Jul
BSL TTL
Aug
Sep
Oct
Nov
Dec
Total Loss%
Asia Pacific
Active-va Fire Loss Reduction - Vietnam
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Key Initiative: Total Fire Loss Reduction for Category Heroes Active & Activa (Vietnam Operations)
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C
AP2165
Key Metrics:
Primary metric (Y): First Fire Loss
= First fire loss (pieces) / total inspection (pieces)
Baseline = 26.76%
Target = 18% (AOP = Baseline)
Secondary metric (y1): Re-fire Loss
= Re-fire loss (pieces) / total inspection in re-fire (pieces)
Baseline = 29.19%
Target = 21% (AOP = Baseline )
TTL Baseline = 45.37%
Target = 29.90% (vs AOP = 36.2%)
= (Clay loss + FF loss + RF loss) / total casting
Measure: 31/03/10
Control: 31/07/10
RF loss
by defect
RF
Loss
- Pareto
Active -va fire loss
90
100
80
30
80
70
25
60
50
40
40
30
20
20
10
0
RF loss Defect
Count
Percent
Cum %
15
CDT
38.27
42.5
42.5
Matt
9.16
10.2
84.2
LE
8.85
9.8
94.1
PRT
3.60
4.0
98.1
Other
1.75
1.9
100.0
100
20
5
RF loss
29.19
43.0
43.0
FF loss
26.76
39.4
82.4
CL loss
11.94
17.6
100.0
0
FF loss by defect
FF
Loss - Pareto
25
10
PHT
28.40
31.5
74.1
80
15
60
10
40
5
20
0
FF loss defect
Count
Percent
Cum %
CCT
16.96
70.5
70.5
LE
3.02
12.6
83.1
PF
2.01
8.4
91.4
WH
1.12
4.6
96.1
Other
0.94
3.9
100.0
Percent
20
0
Fire loss
Count
Percent
Cum %
Percent
60
Count
Business Errors:
- Active –Activa are key models with high/stable demand.
They are strategic products with big benefit. Due to their
high losses, supply of these models could not support
with high demand.
- Sale revenues loss in EBIT about $ 117k annually. We
have shortage around 200 pcs of Active-va / month which
are caused by high fire loss.
- Price increase pressure to maintain GM will impact in lost
sales & revenue
Barriers:
- New model & complex
- Lack of skilled workers – Design not complete- Mold
technical & mold condition not stable
Benefits: (in K USD @ AOP rate)
Direct Saving = 214k USD (98 + 117)
- Production losses = 98k USD
- Sales losses = 117k USD (short supply models)
Cash Flow Improvement = 214K USD
Indirect Saving = Nil
Program
Budget: = Nil
4
Analyze: 31/05/10
Close: 30/09/10
Count
Define: 01/03/10
Improve: 30/06/10
Count
Completion Schedule:
DMAIC
0
High Fire Losses on Active-Va one piece cause high cost and unstable supply
Project Leader: Nguyen Phuong (BB)
Project Champion: Prasanna
MBB: Pittaya
Team Members: Do Anh Thai, Nguyen Ngoc Cang, Nguyen
Lam , Nguyen T Phong , Nguyen Thanh Hai,,Huynh Anh Tuan
,Le Ngoc Hung
Asia Pacific
Active-va Fire Loss Reduction - Vietnam
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Project #
AP2165
Project Title
Active-Va One piece Fire loss reduction
BB
Nguyen Phuong
Champion
Prasanna
M A
I
MBB
Techarungnirun Pittaya
Benefit Category (K USD)
Detailed Computation by Category
DIRECT BENEFIT
Direct Saving from reduction loss = ((Total pcs FF* cost *( Y BSL- Ytarget) +
Total pcs RF *cost *( YBSL - Ytarget))*11.5 month
=97690$
A. Cost Takeout = 97.6
C
B. Incremental Margin
(1) Net Increased Capacity
= 116.6
(2) New Product Net Sales
=
Direct saving from Incremental margin= (Total pcs selling * price selling
*%margin *% improve)11.5 month
=116649$
C. Inc Cost Exec =
AOP Exchange rate = 17,819.65 VND / USD
Total Direct Saving Project = Direct saving from reduction loss + Direct
saving from Incremental margin=214340$
Total Direct Benefit
= 214.3
CASH FLOW BENEFIT
Net Cash = 214.3
INDIRECT BENEFIT
A.Cost Avoidance =
B. Cost Savings =
C. Net NVA Reduction =
D. Non Financial Benefit=
5
Asia Pacific
B. Executive Summary
2. Solution Strategy
 Statistical study high-loss models and defect locations
 Focus team assignment by model
 Beware of new comers (PF, HL,WH,LE)
 Apply Six Sigma tools to identify vital factors (Xs) for process control
 Key factors to study:
 Slip formula, Aging time
 Mold life , mold condition and design variation
 Casting system, tools, skill and procedure variations
 Daily communications among key processes
6
Asia Pacific
B. Executive Summary
Support Activities
 Daily loss court meeting and trouble shooting
- FF major defects
- Defect by models
- Relevant defect locations
- Focus team assignment by product group
- Trouble shooting database and follow up
- Defect traceability road-map and data collection
- Defect location map recording by location
7
Asia Pacific
B. Executive Summary
3. Summary of Six Sigma Tool Application
Measurement Phase
 CTQ flow chart
 Process flow chart
 Process mapping (KPIVs, KPOVs)
 C&E Matrix
 GR&R (A-RF-L)
 Baseline data (FFL, RFL, TTL, % defects)
Analysis Phase
 FMEA summary
 SPC charts
 Multi-vari studies( T-test, One way Anova, …)
 Paretos and location
8
Asia Pacific
B. Executive Summary
3.Six Sigma Tool Application
Improvement Phase
 GR&R (FF result: A,defect CC & LE)
Data mining experiment (interactions of Humidity & Mold life , OPT, Aging time…).
 DOE & RSM
Visual communications (Defect location updates)
 Training (caster master,)
 Casting procedure modification
9
Asia Pacific
B. Executive Summary
3.Six Sigma Tool Application
Control Phase
A. Control Plan
B. Defect tracing and feedback daily
C. Slip SPC and control sheet
D. Humidity & temperature record
E. POKAYOKE & Visual factory
F. Casting procedure follow-up
G. Mold status record
H. Casting procedures follow-up
Performance trend charts
- FFL,RFL, TTL (Ys)
- % of cast loss, CC, PF and new comers (ys)
10
Asia Pacific
B. Executive Summary
4. Results and Conclusions
 Active –va one piece
performance has been improved from
w4.Apr 2010 and achieved stable results through Jul.2010
Trend Chart RF Loss
Time
FF loss %
BSL FF
Ju
n'
10
Ju
l'1
W
0
1.
Au
g'
10
ar
'1
0
Ap
r'1
0
M
ay
'10
M
Ja
n'
10
Fe
b'
10
O
ct
'0
9
No
v'0
9
De
c'0
9
Au
g'
09
Se
p'
09
40.00
30.00
20.00
10.00
0.00
W
1.
Au
g'1
0
Ju
l'1
0
Ju
n'1
0
M
ay
'10
Ap
r'1
0
M
ar
'10
Fe
b'1
0
%
40.00
30.00
20.00
10.00
0.00
Ja
n'1
0
Time
Target FF
RF loss %
BSL RF
Target RF
Trend Chart TT Loss
11
ug
'1
0
W
1.
A
Target %
Ju
l'1
0
Tim%
e
BSL
ay
'1
0
Ju
n'
10
TTL%
M
pr
'1
0
A
ar
'1
0
M
Fe
b'
10
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Ja
n'
10
%
%
Trend Chart FF Loss
Asia Pacific
Monthly saving & YTD summary
OUT PUT INCREASE
DIRECT & INDIRECT SAVING USD
60000.0
Total A pcs increase saving
500
Transfer A
0
Jan'1 Feb' Mar' Apr' May' Jun'1 Jul'1
0
10
10
10
10
0
0
Total A pcs
increase
saving
129
34
42
55
210
216
129
Transfer A
556
221
576
498
741
835
723
40000.0
Total Direct saving $
$
$
1,000
Indirect Saving $
20000.0
0.0
Nov' Dec' Jan' Feb' Mar' Apr' May' Jun' Jul'
Total Direct saving $ 56023005176620153304 322131471178 7048
Monthly
Indirect Saving $
27601738153619332141 263619923814 5338
Monthly
Early Project Saving
12
Asia Pacific
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II. MEASUREMENT PHASE
A. Process Description
B. Process Map Summary
C. Cause & Effects Fishbone Diagram
D. Cause & Effects Matrix Summary
E. GR& R
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Asia Pacific
A. Process Description
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Process Flow Chart
Generator
Air Compressure
Slip Making
Critical
Process
Mold Making
Model/Mold design
Mold fit
Surface quality
Thixo
Residue
Slip pumping
Mold installation
Circulating time
Slip line design
Leakage
Mold maintenace
Bench design
CASTING
Mold prep.
Cleaning
Drying
Mold assembling
Bench prep.
Pouring
Slip rate
Time
Casters
Demolding
Punching
Predrying
Draining
Feedback
Feedback
Sponging
Green finishing
& inspection
Drying
Trap glaze
White inspection
Pass
Casting Environment : Humidity & temperature
Fail
Loss
Fai
Loss
Spraying
Pass
Loss
Glaze
dryness
Loading
Firing
Rework
Glost inspcection
VC Plumbing Vietnam bird-view
• Plant Operation: started Jan. 1997
• Headcount: approx. 300 employees
• Production schedule: 2 shifts x 6 days/week
• Plant Capacity:
14
- Output: avg. 35000“A” pcs/ month
Asia Pacific
Process Map FF Summary
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Asia Pacific
CAUSE & EFFECT FISHBONE DIAGRAM
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Measurements
+ Master meter
pressure
Materials
+ Raw materials Glaze
quality
+ Mold Life
+ Slip Quality
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C
Personnel
+ Plastic Mold
+ Humidity Meter
M A
Caster ,Glost inspector , Kiln
operator, Sprayer
+ Operator skill
+ Duels
Km/l
% FF Loss
-Humidity
-Temperature
- Dirty
-Bast Wash
Environment
16
+ Training procedure
+ Kiln equipment
+ Standard methods
sheet
+ Spray gun
+ Slip Formula
+ Case Mold
+ handling
+ casting tool
Methods
+ Glost equipment
Machines
Asia Pacific
C&E Metric Summary FF
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Asia Pacific
Process Map RF
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Asia Pacific
MEASUREMENT STUDY-GR&R
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Asia Pacific
GR&R (A-RF-L)
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Need Improve more
MS is Acceptable < 10%
20
Asia Pacific
III. ANALYSIS PHASE
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A. FFL% with CCL% correlation
B. High volume defect by
Location focus
C. CCL defect happen high mold life
D. Caster performance on FFL
defect & impact of Aging time to
FFL
E. CDT & PHT defect loss high ratio
on RFL
21
Asia Pacific
FFL% vs CCL % correlation
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High
correlat
ion
CCL vs
FFL
Regression Analysis: FFL % versus CCL %
The regression equation is
CC Defect happen with high ratio >70%FFL
on Active one piece in 2009 Need focus to
improve CCL to reduce FFL
I
FFL % = 5.50 + 1.29 CCL %
Predictor
Constant
CCL %
Coef
SE Coef
T
P
5.496
2.373
2.32
0.033
1.2947
0.1680
7.70
0.000
S = 3.56428
R-Sq = 76.7%
R-Sq(adj) = 75.4%
Analysis of Variance
Source
DF
SS
MS
F
P
1
754.06
754.06
59.36
0.000
Residual Error
18
228.67
12.70
Total
19
982.74
Regression
Unusual Observations
22
Obs
CCL %
FFL %
Fit
SE Fit
Residual
8
11.0
28.194
19.755
0.885
8.439
St Resid
2.44R
Asia Pacific
CCL % BY HIGH VOLUME LOCATION ON PRODUCT
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CCL happen so much on O.A.P.P2,H location
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Picture to illustrate Product location
A
H
H
O
M A
P2,P
Reduce CCL on these
location O,A,P,H to
improve CCL.
23
Asia Pacific
CORRELATION CCL % BY LOCATION VS MOLD LIFE
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Two-Sample T-Test and CI: CCT Loss, Mold Life
Two-sample T for CCT Loss
ML
N
Mean
StDev
SE Mean
High
5
56.40
7.83
3.5
Low
5
22.00
4.00
1.8
Difference = mu (High) - mu (Low)
Estimate for difference:
95% CI for difference:
44.5073)
34.4000
(24.2927,
T-Test of difference = 0 (vs not =):
T-Value = 8.75 P-Value = 0.000 DF =
5
Significant
Mold life high &
Low different
CCL
CCL by location A, H,P happen on mold Which one have high mold
life . Need focus to find out what’s mold life is best setting for
improvement
24
Asia Pacific
CCL DEFECT WITH CATSERS PERFORMANCE
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CCT Loss Defect by Caster
One-way ANOVA: 1070, 1139, 1187, 1293, 1463, 1659, 1666, 1906, 1907
Source
DF
SS
MS
F
P
Factor
8
380.1
47.5
1.38
0.254
Error
25
862.9
34.5
Total
33
1243.0
S = 5.875
R-Sq = 30.58%
R-Sq(adj) = 8.36%
Individual 95% CIs For Mean Based on
Pooled StDev
CCT Loss By caster on Mar’10
Level N
Mean
+---------+
StDev
1070
4
11.000
5.824
(--------*-------)
1139
4
11.675
4.167
(--------*-------)
1187
4
14.825
3.686
1293
4
7.025
4.225
(--------*--------)
1463
4
7.300
3.032
(-------*--------)
1659
4
9.445
7.852
(-------*--------)
1666
4
9.025
6.989
(--------*--------)
1906
3
------)
18.667
10.599
1907
10.400
3.940
3
---------+---------+---------
(-------*--------)
(---------*--(---------*---------)
---------+---------+---------
+---------+
CCT loss between casters have big variation .Specially on ID
7.0
1659 ,1666,1659,1187 & 1097 with big variation & high mean.On
28.0Pooled StDev = 5.875
Mar’ these ID caster continue with CCT loss high %. Need
improve Caster performance
25
14.0
21.0
Asia Pacific
CCL DEFECT WITH SLIP AGING TIME
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Test for Equal Variances for CCL
Aging time
F-Test
Test Statistic
P-Value
2.5
Lev ene's Test
Test Statistic
P-Value
2.9
0
Aging time
29.62
0.000
2
4
6
8
95% Bonferroni Confidence Intervals for StDevs
7.33
0.017
10
Significant different
2.5
2.9
2
4
6
8
10
12
14
16
CCL
On Low aging time 2.5 have variation so much & Mean % CCT defect higher than High
aging time 2.9. So if continue maintain and increase more Aging time to
standardization. We can improve more defect performance
26
Asia Pacific
% RFL BY CDT ,PHT & MATT LOSS DEFECT
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CDT & PHT loss 75% on RFL
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Asia Pacific
Defect loss by kiln No
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Boxplots of CC% by Kiln
(means are indicated by solid circles)
CC%
10
5
0
1
2
Kiln
P>0.05
No difference
between 2 kilns
Two-Sample T-Test and CI: CC%, Kiln
Two-sample T for CC%
Kiln
1
2
N
53
81
Mean
2.56
2.86
StDev
2.10
2.37
SE Mean
0.29
0.26
Difference = mu (1) - mu (2)
Estimate for difference: -0.305
95% CI for difference: (-1.078, 0.468)
T-Test of difference = 0 (vs not =): T-Value = - 0.78
P-Value = 0.436 DF = 120
28
Asia Pacific
FMEA SUMMARY
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IV. IMPROVEMENT PHASE
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A. Rifle Shot study
B. Multi-vari Studies on CCT defect by location
C. Improve mold condition/modification &
Mold life
D. Improve Caster performance/allocation &
Aging time
E. Multi-vari studies on RF loss CDT& PHT
F. Data mining DOE on effects of Mold life &
Humidity
G. Defects monitoring and daily feedback
H. Casting procedures follow-up
30
Asia Pacific
CCT LOSS BY LOCATION NEED TO IMPROVE
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I> O location need to
improve
II> A location need to
improve
Iii> H location need to
improve
IV> P2,P location Need to
improve
31
Asia Pacific
Reduction CCL on location O
D
Rifle Shot study
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Location O : 24% on CCL %
-Poor corner need
=> Change radius dia
-Poor moving short pad
-=> Change pad by soft pillow
-Thickness not enough
Make thicker more 3mm
 Visual oil check
Soft pillow
Visual Oil check
32
Asia Pacific
Reduction CCL on location O
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Significant improve CCL
at O location
One-way ANOVA: Before, After
Source
DF
SS
MS
F
P
Factor
1
293.2
293.2
4.80
0.043
Error
17
1038.1
61.1
Total
18
1331.3
S = 7.814
R-Sq = 22.02%
R-Sq(adj) = 17.44%
Individual 95% CIs For Mean Based on
Pooled StDev
Level
Before
After
N
Mean
StDev
11
12.770
9.552
8
4.813
4.237
--+---------+---------+---------+------(---------*--------)
(-----------*----------)
--+---------+---------+---------+------0.0
5.0
10.0
15.0
Before W3 of Apr’10 After is from W4 of
Apr- W4 of jul’10
Pooled StDev = 7.814
33
Asia Pacific
Reduction CCL on location A
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Location A : 20 % on CCT %
Rifle Shot study
-Humidity at location so hard to control
, Especially at high mold life times
Cheese cloth cover
Air fan to dry
 Green finishing on transfer dryer
date
Air Fan to dry
Standard loose mold
Cheese cloth cover
34
Asia Pacific
Reduction CCL on location A
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Significant improve CCL
at A location
One-way ANOVA: A Before, A After
Source
DF
SS
MS
F
P
Factor
1
300.7
300.7
5.84
0.042
Error
8
411.8
51.5
Total
9
712.5
S = 7.174
R-Sq = 42.21%
R-Sq(adj) = 34.98%
Individual 95% CIs For Mean Based on
Pooled StDevLevel
+---------+---------+---------+-A Before
5
27.309
7.893
A After
5
16.341
6.376
N
Mean
StDev
-------
(----------*----------)
(---------*----------)
-------+---------+---------+---------+-14.0
21.0
28.0
35.0
Pooled StDev = 7.174
Before W1 of May After is from w2 of May – w2 of
Aug’10
35
Asia Pacific
Reduction CCL on location H (Foot core)
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Rifle Shot study
=>New comer : need to improve mold
design : make spagless for foot core .
=> Back up foot core ( 2 foot core for 1
mold set
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Asia Pacific
Reduction CCL on location H (Foot core)
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Two-Sample T-Test and CI: Before, After
Two-sample T for Before vs After
N
Mean
StDev
SE Mean
Before
7
13.83
7.03
2.7
After
8
8.75
2.01
0.71
Difference = mu (Before) - mu (After)
Estimate for difference:
95% CI for difference:
5.07901
(-1.65354, 11.81156)
T-Test of difference = 0 (vs not =): T-Value = 1.85
Value = 0.114 DF = 6
P-
Have improve but not so much . NPD research &
develop mold technical .How to spagless foot core
to control mold humidity
37
Asia Pacific
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•Most of location be reduced CCT loss , just remain P2,P location still not yet
improve .
•So let take action to improve P2,P location in next step
38
Asia Pacific
Reduction CCL on location P2& P
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Rifle Shot study
Do experiment on 1 bench with 1
opt . Result after one month
Location P2,P: is hollow .
=> Modified solid
Result
Significant improve
Two-sample T for before_1 vs after_1
N
Mean
StDev
SE Mean
before_1
8
0.2275
0.0423
0.015
after_1
4
0.06750
0.00957
0.0048
Difference = mu (before_1) - mu (after_1)
Estimate for difference:
95% CI for difference:
0.160000
(0.123757, 0.196243)
T-Test of difference = 0 (vs not =): T-Value = 10.18
Value = 0.000 DF = 8
39
P-
Asia Pacific
Increase Aging time
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I-MR Chart of Aging time1
Individual Value
U C L=3.0504
3.0
_
X=2.9263
2.9
LC L=2.8021
2.8
2
4
6
8
O bser v ation
10
12
14
16
Moving Range
0.16
U C L=0.1525
0.12
0.08
__
M R=0.0467
0.04
0.00
LC L=0
2
Before
40
Aging
time
Ave:
2.92
day
4
6
8
O bser v ation
10
After is from w1 of Jun still Jul’10
12
14
16
After
Asia Pacific
Improve Caster Performance
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ter, 1463 before, 1463 After, 1293 before, 1293 After, 1632 After, 1070 before, 107
Rifle Shot study
40
One-way ANOVA: 1907 Before, 1907 After, 1666 before, 1666 After, ...
DF
SS
MS
F
P
Factor
18
2092.3
116.2
3.94
0.000
Error
35
1031.4
29.5
Total
53
3123.7
S = 5.429
30
R-Sq = 66.98%
Data
Source
10
R-Sq(adj) = 50.0
Individual 95% CIs For Mean Based on
0
Pooled StDev
Level
N
+---------+-----
Mean
StDev
1907 Before
3
17.937
8.362
1907 After
3
4.127
3.606
1666 before
3
6.754
1.537
1666 After
3
3.733
3.607
1139 before
3
7.810
6.769
1139 After
3
6.746
1.787
1463 before
3
11.333
4.163
1463 After
3
8.238
5.918
20
----+---------+--------(----*----)
re er re er re er r e fter or e fter fter ore fter ore fter or e fter or e fter
fo ft f o ft fo ft fo
f
f a ef A ef A ef A
Be 07 A be 66 A be 39 A be 63 A be 93 A 32 A be 70
b 9
B 7
B 4
7 9 66 6 39 1 63 4 93 2
0 0 59 65 87 18 84 18
6
0
7
1 6
1 6
1 1
1 4
1 2
1
1 0
1 1
1 1
1
9
1
1
1
1
1
1
1
1
1
1293 before
---*----)
3
25.317
14.444
1293 After
3
1.111
1.925
(----*----)
1632 After
2
3.095
0.337
(------*-----)
1070 before
3
3.333
5.774
(-----*----)
1070 after
3
3.000
2.646
(----*-----)
1659 before
3
11.746
4.399
1659 After
3
3.333
5.774
1187 Before
3
6.667
2.309
=>Run WCP effectively
1187 After
3
5.333
0.577
-=> Standard casting procedure
1184 Before 1
---*--------)
25.000
*
7.953
2.228
(----*-----)
(-----*----)
(----*----)
(-----*----)
(-----*----)
-=> PP program Effectively & Incentive
(----*-----)
(----*----)
1184 After
3
(-
(-----*----)
(-----*----)
(-----*----)
(----*-----)
(----(-----*----)
Significant improvement Caster Performance
41
Asia Pacific
CCL After VS Before Take Action
D
M A
I
C
Test Mold life
Normal distribution
Two-Sample T-Test and CI: Before, After
Two-sample T for Before vs After
N
Mean
StDev
SE Mean
Before
19
15.31
3.95
0.91
After
13
8.61
2.14
0.59
Significantly CCL improve before
vs After is from May – Jul’10
Difference = mu (Before) - mu (After)
Estimate for difference:
95% CI for difference:
6.70320
(4.48224, 8.92417)
T-Test of difference = 0 (vs not =): T-Value = 6.18
28
42
P-Value = 0.000
DF =
Asia Pacific
Reduction CDT & PHT defect Loss on RF Loss
D
M A
I
C
Rifle Shot study
Boxplot of Normal Program, Special program
24
22
Normal Kiln program
Data
20
18
16
14
Significa
nt
different
between
Kiln
program
Special Kiln program
Set up special kiln
program to run for
Some heavy &
complex model
including : Active to
reduce CDT ,PHT
43
12
10
Normal Program
Special program
Two-Sample T-Test and CI: Normal Program, Special
program
Two-sample T for Normal Program vs Special
program
N
Mean
StDev
SE Mean
Normal Program
7
20.73
1.67
0.63
Special program
7
12.24
1.99
0.75
Difference = mu (Normal Program) - mu (Special
program)
Estimate for difference:
95% CI for difference:
8.48571
(6.32515, 10.64628)
T-Test of difference = 0 (vs not =): T-Value =
8.64 P-Value = 0.000 DF = 11
Asia Pacific
Reduction CDT & PHT defect loss on RF Loss
D
M A
I
C
CDT & PHT Improve
from Nov’09 to
Jul’10
Two-Sample T-Test and CI: PHT% Before, PHT %
After
Two-sample T for PHT% Before vs PHT %
After
Good trend
N
Mean
StDev
SE Mean
PHT% Before
6
6.92
1.69
0.69
PHT % After
7
4.663
0.833
0.32
Difference = mu (PHT% Before) - mu (PHT %
After)
Estimate for difference:
95% CI for difference:
2.25212
(0.45997, 4.04427)
T-Test of difference = 0 (vs not =): TValue = 2.97 P-Value = 0.021 DF = 7
44
Asia Pacific
DOE OBJECTIVE
D
M A
I
C
The DOE was started from 7-Jun To 12 Jul ’10
Key Variable Used : Mold Life , OPT , Humidity , Slip formula, Slip
Aging time
Research interaction of Mold life , Humidity impact to CC Loss defect
on Active one piece
Find out Best combination between mold Life VS humidity with the
best result on Active one piece
45
Asia Pacific
Data mining –CC% vs FACTORS (DOE)
Data mining with coded factors
46
D
M A
I
C
Asia Pacific
DOE-CCL VS MOLD LIFE & HUMIDITY
D
M A
I
C
Tabulated statistics: Mold life, Humidity
Rows: Mold life
off
45
51
57
63
69
75
All
on
All
0.1633
0.0467
0.1050
0.05774
0.04041
0.07791
3
3
6
0.2033
0.1233
0.1633
0.00577
0.03786
0.05007
3
3
6
0.2233
0.1367
0.1800
0.01155
0.00577
0.04817
3
3
6
0.2833
0.1767
0.2300
0.01155
0.03215
0.06229
3
3
6
0.3033
0.2700
0.2867
0.02309
0.03464
0.03204
3
3
6
0.3267
0.3033
0.3150
0.03512
0.02309
0.02950
3
3
6
0.2506
0.1761
0.2133
0.06485
0.09394
0.08806
18
18
36
Cell Contents:
47
Columns: Humidity
Result
:
Mean
Result
:
Standard deviation
Mold life frome 69-75 got high CCL
.So that why we just focus mold life
from 57-63
Asia Pacific
DOE-CCL VS MOLD LIFE & HUMIDITY
D
M A
I
C
ANOVA: Result versus Mold life, Humidity
Factor
Type
Levels
Values
Mold life
fixed
6
45, 51, 57, 63, 69, 75
Humidity
fixed
2
off, on
Analysis of Variance for Result
Source
DF
SS
MS
F
P
Mold life
5
0.188033
0.037607
32.57
0.000
Humidity
1
0.049878
0.049878
43.19
0.000
Error
29
0.033489
0.001155
Total
35
0.271400
S = 0.0339822
48
R-Sq = 87.66%
Mold life &
Humidity
impact so
much to CC
defect loss
70% &
18.3%
R-Sq(adj) = 85.11%
Asia Pacific
DOE – CC% vs Mold life ,humidity ,OPT ( 3 input, 2 level )
D
M A
I
C
Data mining work sheet ( Red- code)
Model
Cast date cast pcs/day
Mold life
Humidity
Humidity1 OPT
Slip formulaAging time loss pcs Result
StdOrder RunOrder Blocks
CenterPt StdOrder_1RunOrder_1
2010
7-Jun 13 45 off
-1
1632 B-36
68
2
0.23
1
1
1
1
1
1
2010
8-Jun 14 51 off
-1
1632 B-36
68
3
0.21
2
2
1
1
2
2
2010
9-Jun 13 57 off
-1
1632 B-36
68
3
0.23
3
3
1
1
3
3
2010
10-Jun 14 63 off
-1
1632 B-36
68
4
0.29
4
4
1
1
4
4
2010
11-Jun 15 69 off
-1
1632 B-36
68
4
0.33
5
5
1
1
5
5
2010
12-Jun 15 75 off
-1
1632 B-36
68
4
0.33
6
6
1
1
6
6
2010
13-Jun 14 45 on
1
1632 B-36
68
0
0.07
7
7
1
1
7
7
2010
14-Jun 14 51 on
1
1632 B-36
68
2
0.14
8
8
1
1
8
8
2010
15-Jun 15 57 on
1
1632 B-36
68
2
0.13
9
9
1
1
9
9
2010
16-Jun 14 63 on
1
1632 B-36
68
3
0.14
10
10
1
1
10
10
2010
17-Jun 13 69 on
1
1632 B-36
68
3
0.23
11
11
1
1
11
11
2010
18-Jun 14 75 on
1
1632 B-36
68
4
0.29
12
12
1
1
12
12
2010
19-Jun 15 45 off
-1
1632 B-36
68
1
0.13
13
13
1
1
13
13
2010
20-Jun 15 51 off
-1
1632 B-36
68
2
0.2
14
14
1
1
14
14
2010
21-Jun 13 57 off
-1
1632 B-36
68
2
0.23
15
15
1
1
15
15
2010
22-Jun 14 63 off
-1
1632 B-36
68
4
0.29
16
16
1
1
16
16
2010
23-Jun 14 69 off
-1
1632 B-36
68
4
0.29
17
17
1
1
17
17
2010
24-Jun 14 75 off
-1
1632 B-36
68
5
0.36
18
18
1
1
18
18
2010
25-Jun 15 45 on
1
1632 B-36
68
1
0.07
19
19
1
1
19
19
2010
26-Jun 13 51 on
1
1632 B-36
68
1
0.08
20
20
1
1
20
20
2010
27-Jun 14 57 on
1
1632 B-36
68
2
0.14
21
21
1
1
21
21
2010
28-Jun 15 63 on
1
1632 B-36
68
3
0.19
22
22
1
1
22
22
2010
29-Jun 14 69 on
1
1632 B-36
68
4
0.29
23
23
1
1
23
23
2010
30-Jun 15 75 on
1
1632 B-36
68
5
0.33
24
24
1
1
24
24
2010
1-Jul 15 45 off
-1
1632 B-36
68
2
0.13
25
25
1
1
25
25
2010
2-Jul 15 51 off
-1
1632 B-36
68
2
0.2
26
26
1
1
26
26
2010
3-Jul 14 57 off
-1
1632 B-36
68
2
0.21
27
27
1
1
27
27
2010
4-Jul 15 63 off
-1
1632 B-36
68
4
0.27
28
28
1
1
28
28
2010
5-Jul 14 69 off
-1
1632 B-36
68
4
0.29
29
29
1
1
29
29
2010
6-Jul 14 75 off
-1
1632 B-36
68
4
0.29
30
30
1
1
30
30
2010
7-Jul 14 45 on
1
1632 B-36
68
0
0
31
31
1
1
31
31
2010
8-Jul 13 51 on
1
1632 B-36
68
2
0.15
32
32
1
1
32
32
2010
9-Jul 14 57 on
1
1632 B-36
68
2
0.14
33
33
1
1
33
33
2010
10-Jul 14 63 on
1
1632 B-36
68
3
0.2
34
34
1
1
34
34
2010
11-Jul 14 69 on
1
1632 B-36
68
4
0.29
35
35
1
1
35
35
2010
12-Jul 14 75 on
1
1632 B-36
68
4
0.29
36
36
1
1
36
36
49
Asia Pacific
DOE – CC% vs Mold life ,humidity ,OPT ( 3 input, 2 level )
D
M A
I
C
Factorial Fit: Result versus Mold life, Humidity, OPT NOTE * This design has some
botched runs. It will be analyzed using a
regression approach.
Estimated Effects and Coefficients for Result (coded units)
Term
Effect
Coef
SE Coef
T
P
0.20979
0.004923
42.61
0.000
0.04046
0.02023
0.001441
14.04
0.000
-0.07208
-0.03604
0.004923
-7.32
0.000
OPT
0.00708
0.00354
0.004923
0.72
0.478
Mold life*Humidity
0.00718
0.00359
0.001441
2.49
0.019
Mold life*OPT
-0.00361
-0.00180
0.001441
-1.25
0.221
Humidity*OPT
-0.02125
-0.01062
0.004923
-2.16
0.040
Mold life*Humidity*OPT
-0.00461
-0.00230
0.001441
-1.60
0.121
Constant
Mold life
Humidity
S = 0.0278501
R-Sq = 92.00%
R-Sq(adj) = 90.00%
Analysis of Variance for Result (coded units)
Source
DF
Seq SS
Adj SS
Adj MS
F
P
Main Effects
3
0.235499
0.203099
0.0676998
87.28
0.000
2-Way Interactions
3
0.012202
0.012202
0.0040674
5.24
0.005
3-Way Interactions
1
0.001981
0.001981
0.0019811
2.55
0.121
28
0.021718
0.021718
0.0007756
Lack of Fit
16
0.009668
0.009668
0.0006042
0.60
0.830
Pure Error
12
0.012050
0.012050
0.0010042
35
0.271400
Residual Error
Total
50
Main effect Mold life , Humidity
Interaction : Mold life & Humidity
Asia Pacific
Reduce model
DOE – red code . OPT exclude
D
M A
I
C
Factorial Fit: Result versus Mold life, Humidity
* NOTE * This design has some botched runs.
using a
It will be analyzed
regression approach.
Estimated Effects and Coefficients for Result (coded units)
Term
Effect
Coef
SE Coef
T
P
0.21333
0.005011
42.57
0.000
0.04200
0.02100
0.001467
14.31
0.000
-0.07444
-0.03722
0.005011
-7.43
0.000
0.00838
0.00419
0.001467
2.86
0.007
Constant
Mold life
Humidity
Mold life*Humidity
S = 0.0300661
R-Sq = 89.34%
R-Sq(adj) = 88.34%
Analysis of Variance for Result (coded units)
Source
P
DF
Seq SS
Adj SS
Adj MS
F
Main Effects
0.000
2
0.235098
0.235098
0.117549
130.04
2-Way Interactions
0.007
1
0.007375
0.007375
0.007375
8.16
32
0.028927
0.028927
0.000904
8
0.006394
0.006394
0.000799
24
0.022533
0.022533
0.000939
35
0.271400
Residual Error
Lack of Fit
0.569
Pure Error
Total
51
0.85
Mold life, Humidity & Interaction ML &
Humidity impact to CC loss
Asia Pacific
DOE – Fractional factorial ( red code )
D
M A
I
C
Interaction Plot (data means) for Result
0.300
Mold
life
57
63
0.275
Mean
0.250
0.225
0.200
0.175
0.150
off
on
Humidity
Mold life , humidity effect so much to CC%
Let do with 2 factors , 3 replicates with 3
center point ( mold life 57& 63)
52
Asia Pacific
DOE –Full factorial s
D
Factorial Fit: Result versus mold life, humidity
M A
I
C
Estimated Effects and Coefficients for Result (coded units)
Term
Effect
Coef
SE Coef
T
P
0.19417
0.011286
17.20
0.000
0.01167
0.00583
0.011286
0.52
0.614
humidity
-0.06444
-0.03222
0.009215
-3.50
0.004
mold life*humidity
-0.00833
-0.00417
0.011286
-0.37
0.718
-0.02250
0.019547
-1.15
0.270
Constant
mold life
Ct Pt
S = 0.0390950
R-Sq = 51.77%
Ct Pt not
significant &
curvature not
significant
R-Sq(adj) = 36.93%
Analysis of Variance for Result (coded units)
Source
DF
Seq SS
Adj SS
Adj MS
F
P
Main Effects
2
0.0190972
0.0190972
0.0095486
6.25
0.013
2-Way Interactions
1
0.0002083
0.0002083
0.0002083
0.14
0.718
1
0.0020250
0.0020250
0.0020250
1.32
0.270
13
0.0198694
0.0198694
0.0015284
1
0.0017361
0.0017361
0.0017361
1.15
0.305
12
0.0181333
0.0181333
0.0015111
17
0.0412000
Curvature
Residual Error
Lack of Fit
Pure Error
Total
53
Let use RSM to
analysis
Asia Pacific
DOE – RSM ( contour plot)
D
M A
I
C
Response Surface Regression: Result versus mold life, Humidity1
The analysis was done using coded units.
Estimated Regression Coefficients for Result
Term
Coef
SE Coef
T
P
Constant
0.171667
0.015960
10.756
0.000
mold life
0.005833
0.011286
0.517
0.614
Humidity1
-0.032222
0.009215
-3.497
0.004
mold life*mold life
0.022500
0.019547
1.151
0.270
mold life*Humidity1
-0.004167
0.011286
-0.369
0.718
S = 0.03909
R-Sq = 51.8%
R-Sq(adj) = 36.9%
Analysis of Variance for Result
Source
DF
Seq SS
Adj SS
Adj MS
F
P
Regression
4
0.021331
0.021331
0.005333
3.49
0.038
Linear
2
0.019097
0.019097
0.009549
6.25
0.013
Square
1
0.002025
0.002025
0.002025
1.32
0.270
Interaction
1
0.000208
0.000208
0.000208
0.14
0.718
13
0.019869
0.019869
0.001528
1
0.001736
0.001736
0.001736
1.15
0.305
12
0.018133
0.018133
0.001511
17
0.041200
Residual Error
Lack-of-Fit
Pure Error
Total
Not different with inferential applied
54
Asia Pacific
Conclusion of DOE
D
Tabulated statistics: mold life, Humidity
Rows: mold life
M A
I
C
Monthly cost comparison between mold life and loss reduction
Columns: Humidity
compare cost by Mold life used
$4,000
60
63
All
All
0.2300
0.1350
0.1825
0.00000
0.00707
0.05500
2
2
4
0.1850
0.1500
0.1675
0.02665
0.00894
0.02633
Cost of mold
2127.26
mold life used 55
2088.5
420.85
391.42
2900.81
Average cost of CCT due to mold life
> 55 casting times
. This will happen
only when we use mold life > 55
times (not happen every month)
0.03536
0.07500
0.00
2
2
4
0.2150
0.1500
0.1825
0.04790
0.01700
0.04833
10
10
20
Count
Best Setting : Here We see at Mold life 60 result
still in target , so we select mold life 60 we will
saving mold life cost 90 $ / 2 months . So Mold
life 60 with Humidity on is best setting
Microsoft Excel
Worksheet
Compare loss cost
CCT loss on ML >55
ML used at 55
2000.00
0.00000
Standard
Total cost
287.04
1000.00
:
Labour cost for Labour cost for
mold making
operation
308.62
0.2275
result
$287$391
1531.6
0.1650
Mean
mold life used 75
mold life used 55
mold life used 75
0.2900
:
$309$421
$0
12
result
$2,127
$2,089
$1,532
$1,000
6
deviation
55
$2,000
6
Cell Contents:
$2,901
$3,000
1459.53
500.00
This incremental cost
happens every month
with the same amount
1,460
1500.00
773.55
$
57
on
$
off
774
Average
monthly saving
= $ 686
Loss cost
Annual cost comparison between mold life and loss reduction
Change mold every 75
casting times
Average CCT defects of
52% happen during mold
life of 55 – 75
75 casting
times
55 casting
times
Month
0
Month
2.3
Mold life line
Assumptions
1.Avg volume = 1170
casting / month or 1076
firing / month
2. Timing of high CCT
defect = 0.84 month /
each 75-casting time
mold life
Month
3
Month
9
Month
6
CCT reduction 100% from cutting mold life to 55
CCT loss
Incremental
Monthly
Mold life on Mold monthly cost cost from
life >55
from mold
CCT
75
52%
55
0%
Month
12
100%
# Month
impact /
year
5,237
773.55
Saving from reducing mold life to 55 casting times
Annual
Impact
3.34
17,514.33
12.00
9,282.58
8,231.75
= 3.34 months / year
Asia Pacific
V. CONTROL PHASE
D
M A
I
C
C
C
A. Control Plan
B. Defect tracing and feedback daily
C. Slip SPC and control sheet
D. Humidity & temperature record
E. POKAYOKE & Visual factory
F. Casting procedure follow-up
G. Mold status record
H. Caster Performance record
56
Asia Pacific
CONTROL PLAN
D
57
M A
I
C
C
Asia Pacific
DEFECT TRACEBILITY DATABASE
D
58
M A
I
C
C
Asia Pacific
DEFECT TRACEBILITY SHEET
D
M A
I
C
C
Daily check and record all defective pcs for quick tracing, actions and feedback
59
Asia Pacific
DEFECT TRACING AND FEEDBACK
D
M A
I
C
C
Trouble shooting Analysis
60
Asia Pacific
MOLD STATUS DAILY MONITORING
D
M A
I
C
C
Broken mold
61
Asia Pacific
DAILY SLIP CONTROL SHEET
D
62
M A
I
C
C
Asia Pacific
SLIP ONLINE CONTROL
D
63
M A
I
C
C
Asia Pacific
HUMIDITY & TEMPERATURE Record
D
Boxplot of DA 9h Aug, DA 9h Jul, DA 9h jun, DA 9h May
Boxplot of DA 14H Aug, DA 14h jul, DA 14H Jun, DA 14h May
80
M A
I
C
C
Boxplot of DA 5h Aug, DA 5h JUl, DA 5h JUn, DA 5h May
90
80.0
80
77.5
70
70
50
75.0
60
Data
Data
Data
60
50
72.5
70.0
40
67.5
40
30
30
65.0
20
DA 9h Aug
64
DA 9h Jul
DA 9h jun
DA 9h May
DA 14H Aug
DA 14h jul
DA 14H Jun
DA 14h May
DA 5h Aug
DA 5h JUl
DA 5h JUn
DA 5h May
Asia Pacific
POKAYOKE APPLY & VISUAL FACTORY
D
M A
I
C
C
Preventiv
e risk CC
defect
while trap
glaze at
Spray
Dept
Fix location
when run Air
Fan
65
Asia Pacific
DAILY CASTING PROCEDURE FOLLOW-UP
D
M A
I
C
C
Base on Slip property , mold life to set up casting record according daily
66
Asia Pacific
Caster Performance Tracking
D
M A
I
C
C
Daily ,Weekly & monthly Individual caster performance be tracked & feedbacked
67
Asia Pacific
FMEA SUMMARY
D
68
M A
I
C
C
Asia Pacific
VI. RESULTS SUMMARY
A. FFL ,RFL & TTL% PERFORMANCE
B. PROJECT SAVING
69
Asia Pacific
PROJECT RESULTS
Performance FFL % compare before Action
One-way ANOVA: FFL % before, FFL% After
Normal distribution
Source
DF
SS
MS
F
P
Factor
1
463.2
463.2
44.66
0.000
Error
10
103.7
10.4
Total
11
567.0
S = 3.221
R-Sq = 81.70%
R-Sq(adj) = 79.87%
Individual 95% CIs For Mean Based on
Pooled StDev
Level
N
Mean
--------+---------+
StDev
FFL % before
(----*-----)
7
26.116
3.910
FFL% After
5
13.513
1.733
---------+---------+-
(-----*-----)
---------+---------+-
--------+---------+
15.0
25.0
30.0
Pooled StDev = 3.221
20.0
Significantly
Improved from Apr-jul’10
Target 18% Significantly archived
70
Asia Pacific
PROJECT RESULTS
Result RF Loss after took action
One-way ANOVA: RFloss Bfeore_1, RFlossSignificant
After_1 improved
from Nov’09 to jul’10
Normal distribution
Source
DF
SS
MS
F
P
Factor
1
2046
2046
11.88
0.004
Error
13
2239
172
Total
14
4286
S = 13.12
R-Sq = 47.74%
R-Sq(adj) = 43.73%
Individual 95% CIs For Mean Based on
Pooled StDev
Level
N
Mean StDev
------+---------+---------+
RFloss Bfeore_1 10
(-------*------)
39.09
15.71
RFloss After_1
--------)
14.31
2.21
5
---------+---
(----------*---------+---
------+---------+---------+
12
24
36
48
Pooled
StDevarchived
= 13.12
Target 21%
Significantly
Boxplot of RFloss Bfeore_1, RFloss After_1
71
Asia Pacific
PROJECT RESULTS
Significant improved
from W1 of Apr to w4
of Jul’10
Result TT Loss after took action
One-way ANOVA: Before, After
Normal distribution
Source
DF
SS
MS
F
P
Factor
1
2487.4
2487.4
34.67
0.000
Error
22
1578.4
71.7
Total
23
4065.7
S = 8.470
59.41%
R-Sq = 61.18%
R-Sq(adj) =
Individual 95% CIs For Mean Based on
Pooled StDev
Level
N
Mean
StDev
------+---------+-----Before 14 47.838
(-----*-----)
After
10
27.188
---+---------+---
10.639
3.446
(------*------)
---+---------+---
------+---------+-----24.0
32.0
Target 29.1%40.0
Significantly 48.0
archived
Pooled StDev = 8.470
72
Asia Pacific
SAVING RESULT
AP2165 - MONTHLY PROJECT SAVING
73
Asia Pacific