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Black belt Project -Process optimization DV Cyl Head.pptx
1. Slide number: 1
SSBBW3(1)
Six Sigma Black Belt Project
Organization ZF INDIA
Plant Vadu Bk
Black Belt Mr. VL Bhoknal
Sponsor NA
Team Members Mr. Hussain
Mr. Vishal Gaikwad
Date of start 23/01/2015
3. Slide number: 3
SSBBW3(1)
SN Parameter Description
1 Process selected Spring cup spot face milling
2 Part number selected for
study
DV0.007.20.0.00
3 Machine selected for study HMC Mazak 2962
4 Other similar part numbers
where the optimal setting
can be deployed
---
5 Responses Description Type of
response
(Var/Att)
Specification
Distance of 38 mm
spot face from
bottom side
Variable 86+/- 0.1mm from
bottom side
( 44 +/-0.1 from top
side)
Planning
4. Slide number: 4
SSBBW3(1)
SN Parameter Description
1 Current cycle time Current Cycle Time of Mazak machine( m/c no 2962)
is 72 minutes
Planning
Basis of Project selection
Cycle
time
34
75
83 87 90 92 95 98 99 100
0.00
20.00
40.00
60.00
80.00
100.00
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9 10 11
Contribution
in
%
Pareto analysis forprocess cycle time
5. Slide number: 5
SSBBW3(1)
SN Parameter Description
1 Current cycle time Current Cycle Time of spring cup spot face milling
Operation is 462 seconds , i.e. 7.7 minutes
Planning
Basis of Project selection
Pareto analysis for process cycle time
60 65 69 73 78 82 86 89 93 95 97 99 100
53
27
0.00
2.00
4.00
6.00
8.00
10.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0.00
20.00
40.00
60.00
80.00
100.00
Contribution
in
%
Cycle
time
6. Slide number: 6
SSBBW3(1)
Planning
Phase
Jan 2015 Feb 2015 Mar 2015
W1 W2 W3 W4 W1 W2 W3 W4 W1 W2 W3 W4
Planning
Analyse
Improve
Control
Plan Actual Status
Phase Start date Completion
date
Start date Completion
date
Planning 18-Jan-2015 30-Jan-2015 18-Jan-2015 28-Jan-2015 Completed
Analyse 01-Feb-2015 13-Feb-2015 01-Feb-2015 16-Feb-2015 Completed
Improve 15-Feb-2015 27-Feb-2015 16-Feb-2015 26-Feb-2015 Completed
Control 01-Mar-2015 20-Mar-2015 01-Mar-2015 27-Mar-2015 Completed
14. Slide number: 14
SSBBW3(1)
To identify whether parameters
and levels are correct
Full Factorial Analysis
( as nos. of design parameters are less than 3)
Step # 1
Analyse
Objective
DOE Technique / Tool Used
15. Slide number: 15
SSBBW3(1)
Test - Setting + Setting
1st Run 0.01 0.03
2nd Run 0.02 0.05
3rd Run 0.02 0.04
Median 0.02 .04
Range 0.01 0.02
D ( Difference Between Two
Medians )
.02
d = Average of Two Ranges .015
D/d 1.33
Analyse : For Response variation in Depth of spring cup
16. Slide number: 16
SSBBW3(1)
D/d ratio is 1.33, it is more than 1.25 and
less than 3. and there is no overlap.
Hence Parameters identified are correct.
Factorial Analysis : As the approach parameter has
no effect of on variation in depth, hence factorial analysis
is done for only 2 parameter.
Analyse : Step # 1
Next Step
Conclusion
18. Slide number: 18
SSBBW3(1)
Interpretation of Contribution
Analyse : Step # 4 – Factorial plots
As we change cutter speed from –ve setting to +ve setting,
response decreases by 0.005 and
As we change cutter feed from –ve setting to +ve setting,
response increases by 0.025
As we change both parameter from –ve setting to +ve setting,
response decreases by 0.005
23. Slide number: 23
SSBBW3(1)
Validation using B vs C
1 Part number selected for validation DV0.007.20.0.00
2 Better Condition Cutter speed 80 meter/min, feed 0.2 mm /rev,
approach 20 mm
Current Condition Cutter Speed 50 meter/min, Feed 0.15 mm /
rev, Approach 10 mm
3 Sample size 3
4 Sample type Pieces
5 Response decided for monitoring 1) Cycle Time of operation
2) Variation in depth
6 Lot quantity (for batches) N.A.
Improve
24. Slide number: 24
SSBBW3(1)
Data obtained during validation for variation in depth( Quality Parameter )
Piece / Lot Better ( B ) Current ( C )
1 0.04 0.01
2 0.05 0.02
3 0.05 0.02
Improve
25. Slide number: 25
SSBBW3(1)
Analysis - B Vs C
Improve
Piece / Lot Better ( B ) Current ( C )
1 0.04 0.01
2 0.05 0.02
3 0.04 0.02
Median 0.04 0.02
Range 0.01 0.01
D 0.02
d 0.01
D/d ratio 2
Conclusion – As D/d ratio is less than 3, Optimal settings identified are
correct
26. Slide number: 26
SSBBW3(1)
Data obtained during validation for cycle time
Piece / Lot Better ( B ) Current ( C )
1 272 462
2 270 458
3 269 464
Improve
27. Slide number: 27
SSBBW3(1)
Analysis - B Vs C for cycle time
Improve
Piece / Lot Better ( B ) Current ( C )
1 272 462
2 270 458
3 269 464
Median 270 462
Range 3 6
D 192
d 4.5
D/d ratio 43
Conclusion – As D/d ratio is greater than 3, Optimal settings identified are
correct
28. Slide number: 28
SSBBW3(1)
Analysis - B Vs C
1 Process and part number
selected for validation
DV0.007.20.0.00
2 Average of B 270
Average of C 461
3 Xb – Xc
(Amount of Improvement)
191
4 Sigma (B) 1.53
5 K value ( at 95% CL ) 4.2
5 Is Xb-Xc greater than
k*Sigma (b)
Yes
Improve
Conclusion – This proves that cycle time on DV Cylinder head spring cup
spot face milling will be reduced by 191 second at 95% confidence level
29. Slide number: 29
SSBBW3(1)
Conclusion - B Vs C
Improve
By changing process parameters on DV Cylinder
Head spring cup spot face milling from old settings to
new setting, cycle will be reduced by 191 seconds
without affecting quality parameters.
Conclusion
32. Slide number: 32
SSBBW3(1)
Control
Work Standard Correction for Standardization
KPS Sheet Before KPS Sheet After
Page 1 of 3
iklaao-skr Aa^[-la [-ijansa ila.
puNao 411 003
Tula caoMja [MsT/@Sana
SaIT
kampaonaMT isalaoMDr hoD
D/a[-ga nambar DV0.007.01.0.**
Aa^proSana
nambar
0300
Aa^proSana
Ta^p saa[-D ifnaISa
maSaInaIMga kra
maSaIna nambar 2962
maSaIna maJaak - V655
if@car nabar
maToiryala kasT Aayana-
maa^Dola DV - 10
Anau
k`.
Aa^proSana TuilaMga
baIna
naM.
@vaa
MiTTI
caoMja
krNyaavaI
if`@vaoMsaI
spID fID
(rpm)
(mm/mi
n)
9
ra^kr kvhr maa]MTIMgacyaa
haolacao T^pIMga kra
T^p M8 x1.25 9309410000 1 - 1194 1492
10
sava- haolsanaa caamfrIMga
kra
f 28.5 caamfr
kTr
94202601 1 - 670 168
11 spa^T fosaIMga kra
f 38 spa^T fosa
kTr
NA 1 - 530 80
12
Da^vhola haolacao iD/laIga
kra
iD/la f 17.5 NA 1 - 3744 562
Approved
By:
Manufacturing
Engg.
Production Quality Assurance Original Date: 18.12.2008
Date of
Revision:
Page 1 of 3
iklaao-skr Aa^[-la [-ijansa ila.
puNao 411 003
Tula caoMja [MsT/@Sana SaIT
kampaonaMT isalaoMDr hoD
D/a[-ga nambar DV0.007.01.0.**
Aa^proSana
nambar
0300
Aa^proSana
Ta^p saa[-D ifnaISa
maSaInaIMga kra
maSaIna nambar 2962
maSaIna maJaak - V655
if@car nabar
maToiryala kasT Aayana-
maa^Dola DV - 10
Anau
k`.
Aa^proSana TuilaMga
baIna
naM.
@vaa
MiTTI
caoMja
krNyaavaI
if`@vaoMsaI
spID fID
(rpm)
(mm/min
)
9
ra^kr kvhr maa]MTIMgacyaa
haolacao T^pIMga kra
T^p M8 x1.25 9309410000 1 - 1194 1492
10
sava- haolsanaa caamfrIMga
kra
f 28.5 caamfr
kTr
94202601 1 - 670 168
11 spa^T fosaIMga kra
f 38 spa^T fosa
kTr
NA 1 - 795 106
12
Da^vhola haolacao iD/laIga
kra
iD/la f 17.5 NA 1 - 3744 562
Approved
By:
Manufacturing
Engg.
Production Quality Assurance Original Date: 18.12.2008
Date of
Revision:
20.3.2015
Revision No.: 01
MEF/15/01
33. Slide number: 33
SSBBW3(1)
To decide On line monitoring method
for the parameter
Variation Analysis
Analysis # 1
Control
Objective
DOE Technique / Tool Used
35. Slide number: 35
SSBBW3(1)
Control
Multivari Analysis
TIME
BLOCK 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
0.02 0.04 0.03 0.03 0.03 0.03 0.02 0.03 0.03 0.04 0.04 0.02 0.02 0.04 0.04 0.03 0.04 0.02 0.04 0.01 0.04 0.04 0.01 0.03 0.02
0.02 0.03 0.03 0.03 0.02 0.03 0.03 0.04 0.03 0.03 0.04 0.04 0.02 0.03 0.04 0.03 0.02 0.03 0.04 0.04 0.04 0.03 0.03 0.04 0.04
0.05 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.03 0.03 0.04 0.03 0.03 0.05 0.03 0.04 0.04 0.04 0.04 0.02 0.01 0.03 0.03 0.03
PART T0
PART
VARIATION
0.03 0.01 0.01 0.01 0.02 0.01 0.02 0.01 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.00 0.02 0.02 0.00 0.03 0.02 0.03 0.02 0.01 0.02
0.03
TIME TO
TIME
VARIATION
0.03 0.04 0.03 0.03 0.03 0.03 0.03 0.04 0.03 0.03 0.04 0.03 0.02 0.03 0.04 0.03 0.03 0.03 0.04 0.03 0.03 0.03 0.02 0.03 0.03
0.02
Part to part variation is 0.03
Time to time variation is 0.02
Part to part variation is higher
36. Slide number: 36
SSBBW3(1)
Control
Analysis of Data
Part Details
Characteristic Depth Part Number DV0.007.20.0.00 Gage Number
Measurement
unit
mm Part
Description
DV Cylinder
Head
Gage
Description
Target Value 44.00 Least Count
Tolerance +/- 0.1 Study Date 05-mar-2015 Gage R&R
value
USL 44.01 Shift General Gage Bias &
Uncertainty %
LSL 43.9 Any Other Details :-
Data Grouping and Sample Details
Number of Groups
( No.of Time blocks X No.of Streams )
25
Number of Samples in each Group
( It is preferable to collect 5 samples continuously from
the process so that inherent variations are captured )
3
37. Slide number: 37
SSBBW3(1)
Control
Checking the Consistency of Part to Part Variation ( Step 7 )
Average Range ( R bar )
( Round off to one more decimal than data )
0.03 R chart
Upper Control limit ( UCL ) = D4*R bar
( Round off to the same decimal as data )
0.075
Lower Control limit ( LCL ) = D3*R bar 0
Is the Part to Part Variation Consistent ? Yes
If the Part to Part Variation is not consistent , ! STOP ! Do not proceed further. Plan for DOE.
Is the Range Chart plotted ? Yes
Are the Stratification levels more than 3 ? Yes
If the Stratification <= 3, then the Part to Part Variation is very less and the parameter does not require
any monitoring. ! STOP ! Do not proceed further.
Are there 7 consecutive points increasing /
decreasing / one side of mean range ?
No If Yes , write causes ( if possible ) …….
If the range contains patterns as described above , ! STOP ! . Do not proceed further . Plan for DOE .
38. Slide number: 38
SSBBW3(1)
Control
Estimating Part to Part Variation
σ = R bar / d2
( Round off to one more decimal than data )
0.017 Histogram
6 X σ
( Round off to the same decimal as data )
0.104
Overall Average
( Round off to one more decimal than data )
44.01
Construction of Histogram
Does the Overall Average lie in the group
having maximum frequency or in the adjecent
groups ?
Yes
Is there a gradual decreasing trend in frequency
on both sides of the group having maximum
frequency ?
Yes
Are there Two modes ? ( Two groups having
maximum frequency) and both the groups are
distinctly seperated ?
No
Based on above analysis, can you conclude that
Histogram is normal ?
Yes
39. Slide number: 39
SSBBW3(1)
Control
Rejection analysis using Sigma
( Only for Normal Distributions )
Average 44.01 Z USL = ( USL – Average ) / σ 5.5
σ 0.017 Z LSL = ( Average – LSL ) / σ 0
6 X σ 0.1 Projected rejection % above USL Zero
USL 44.1 Projected rejection % below LSL 0
LSL 43.9 Cpk = Z USL / 3 , ZLSL / 3 1.8
Six Sigma Analysis
6 σ <= 75 % of Tolerance
6 σ > 75 % of Tolerance and <= 100 % of Tolerance
6 σ > Tolerance
40. Slide number: 40
SSBBW3(1)
Control
Actions Decided based on Six Sigma Analysis
6 σ <= 75 % of Tolerance 6 σ > 75 % of Tolerance and <=
100 % of Tolerance
6 σ > Tolerance
Actual Part to
Part Variation <=
50% of tolerance
Actual Part to
Part Variation >
50% of tolerance
Use Average & Range chart for
monitoring with 100% inspection
Do DOE to reduce Variation
Use Pre-Control
chart for
monitoring
Use Average &
Range chart for
monitoring
Do DOE to reduce Variation or to
question the tolerance of the
parameter
Remove 100% inspection if done on
this parameter
41. Slide number: 41
SSBBW3(1)
Control
Project Summary
Time taken for project completion : 3 months
Tools / Techniques Used : Process Optimisation
B v/s C
Multivary Analysis
Optimal Setting of design parameters : Cutter speed : 80 meter/ min
Cutter Feed : 0.2 mm/rev
Optimal setting implementation date : 16-Feb-2015
Control method implementation date : 25-Mar-2015
42. Slide number: 42
SSBBW3(1)
Tangible Benefits derived through the project
Intangible benefits derived through the project
Control
1 Cycle time reduced from 492 seconds to 270 seconds
2 Productivity increased from 10 nos. per shift to 11 nos. per shift
3 Annual cost saving : Rs. 1,20,000 .00 (Rs. 1.2 Lakhs.)
4 Throughput time reduction by 4 minutes
1 Knowledge of process optimization technique
2 Knowledge of Multi vary analysis
3 Knowledge of Minitab software for data analysis
