Breakthrough Process Improvement case study – Gold Prize winning submission by SRF Overseas Ltd during 3rd Continual Improvement & Innovation Symposium organized by Dubai Quality Group's Continual Improvement Subgroup to celebrate World Quality Day 2011

1. To reduce the flue gas SPM value
of Biomass boiler
SIX SIGMA BLACK BELT
PROJECT
Team Leader : M. Suresh ( Six Sigma Black belt )
Team Members : P. Sureshbabu
A.Narayanan
G. Ramakrishnan
R.Balakumar
• Technical Textiles Business - Manali 1

2. SRF Group
Gross Turnover: INR 22,792 Mn#
Domestic Domestic
Leader* Leader*
Technical Textiles Packaging Films Chemical & Polymer
Business (TTB) (PFB) Business (CPB)
Bi-axially Oriented Polyester Refrigerants,
Tyrecord,
film Chloromethanes,
Belting ,
Fluorospecialities
Coated Fabrics &
Nylon & other Engineering
Industrial Yarn
plastics
Revenue by Business Segment
Global Position PFB, 14%
Belting Fabrics
2
TTB, 56%
Tyre Cord Fabrics 2
in Nylon 6 TCF CPB, 30%
•Acquisition of businesses of SRF Polymers Ltd. by SRF Ltd. effective from Jan 1, 2009
1 TCF and BF # Inc. SRF Overseas
2 Refrigerants & N6 Segment
2

3. SRF product applications
A] Technical Textiles
Yarn Greige Fabric Dipped Fabric
Nylon Tyre cord used as reinforcement in Tyres
Belting Fabrics
Coated Fabrics
3

4. SRF product applications
B] Packaging Films
C] Chemicals
Refrigerant Gases
Chloromethanes & Fluorospecialities
4

5. Manali, SRF Group - Locations
Tamil Nadu
Gummidipoondi,
Tamil Nadu
Dubai, UAE
Gwalior, Madhya
Pradesh
Trichy, Employees 3000
Tamil Nadu Sites = 9
Bhiwadi,
Rajasthan
Kashipur,
Uttaranchal
Indore,
Corporate Office, Gurgaon, Haryana Madhya Pradesh
5

6. •The first nylon tyre cord company outside Japan to be awarded the Deming Prize in Oct.’2004
•Jamshedji Tata Award conferred on Mr. Arun Bharat Ram, our Chairman, from the Indian Society for
Quality (ISQ) for the year 2006
•Platinum Award for Safety by Greentech Foundation (Chemical Business)
•Platinum award for Environment from Greentech Foundation (Chemical Business)
•Responsible Care Logo from ICC
•Our manufacturing units awarded following certifications:
•ISO 9001
•ISO 14001
•OHSAS 18001
•SA 8000 certification for Chemicals Business plant
6

7. Define - Step A: Identify Project CTQ‟s
Theme selected from BM themes - APC 2009-10
Source of Project idea – Internal problems
DMAIC 7

8. Define - Step A: Identify Project CTQ‟s
PROJECT CTQ:
To reduce the flue gas SPM value of Biomass
boiler
From 156 ppm to less than 100 ppm
Start Date : 12.12.09
End date : 25.09.10
CUSTOMERS: Internal customers- Polymerization , Spinning, RO plant and R & D
External customers- Nearby resident peoples
VOICE OF CUSTOMERS:
Fly ash should not be scattered to the nearby areas- Resident people.
Flue gas SPM value should not cross 150 ppm – Pollution Control Board.
Biomass steam boiler should run continuously – Internal customers.
DMAIC 8

9. Define - Step A: Identify Project CTQ‟s
BACK GROUND :
• Steam is the main source of heating in Poly & Spinning processes.
• Steam was produced using Oil Fired Boiler (Furnace Oil) till March 2007 in TTBM.
• Biomass Steam Boiler commissioned during March 07 for reducing the steam cost.
Steam cost in Rs/MT
By reducing the fuel
2500 cost with alternate fuel
1960
BETTER
for steam generation -
2000
57 % Reduction Solid fuel (Rice Husk)
Steam cost Rs/ MT
1500
1000 845
500
0
Rice husk
Oil fired boiler Biomass boiler Rice husk is fired
in biomass
Fuels used in Biomass boiler : steam boiler for
1. Coal - 100% steam
generation
2. Rice husk – 50% & coal- 50 %
3. Rice husk – 50% & Groundnut shell 50%
Rice husk and coal will be available throughout the year and
groundnut shell is a seasonal fuel available only 3 months per year
Biomass boiler
DMAIC 9

10. Define - Step B: Develop Team Charter
Business Case:
SPM value is defined as the suspended particulate matter in the flue gas which is emitted through
the chimney. This value is recorded in the centre of the chimney.
TNPCB Norm -SPM – 150 ppm
At present Avg SPM value is 156 PPM & Peak SPM value is 195 PPM.
Biomass boiler SPM value trend Fly ash
complaints
250
increased after
using 100% BETTER
225 rice husk
100% coal
TNPCB restricted the
usage & 50%
200 usage of coal since
rice husk and
Manali falls in red
50% coal
zone area. So 100%
SPM value in PPM
175 usage as fuel
rice husk started
combinations
using in biomass
150 boiler from Mar 09
125 Avg 100 PPM
100
100
75
Target- 0
50
09
M 09
D 7
S 8
A 9
F 7
Ju 7
Ju 8
Ju 9
S 9
N 9
M 7
7
A 8
M 8
8
M 9
9
8
9
A 7
A 9
et
0
0
0
-0
-0
-0
-0
0
-0
0
-0
-0
0
-0
0
-0
-0
-0
-0
-0
v-
-
l-
l-
l-
g
g-
r-
r-
r-
n
ec
ct
ay
n
eb
ay
n
ay
n
ep
ep
ar
ar
ar
Ju
Ju
Ju
p
p
p
o
Ja
u
O
M
T
THEME: REDUCE THE FLUE GAS SPM VALUE FROM 156 TO < 100 ppm-Target –Jun 2010
DMAIC 10

11. Define - Step B: Develop Team Charter
On line Stack monitoring system ( SPM ) introduction in Biomass boiler and heater
Data transfer
through internet
Computer Computer
Data trend TNPCB server
in SRF in Guindy
local computer
Biomass stack
Project cost PARTICULARS Rs. (in lacs)
SPM ANALYSER (Basic equipment) 5.9
DATA ACQUISITION SOFTWARE 2.8
ACCESSORIES, ERECTION & COMMISSIONING CHARGES 1.4
TOTAL 10.0
11

12. Define - Step B: Develop Team Charter
On line Stack monitoring system ( SPM ) introduction in Biomass boiler
SPM data is transferred to TNPCB Guindy office through internet.
SPM spec less than 150 ppm. Corrective action need to be taken immediately for any
Value above 150 ppm otherwise boiler has to be stopped.
12

13. Define - Step B: Develop Team Charter
Business Case:
By doing this project we can save up to Rs 34 Lacs/annum and if we are not doing it
now we will incur Rs 34 Lacs/annum and thereby increasing steam cost.
Problem statement:
For the past one year we have incurred Rs 34 Lacs / annum excessively in biomass
boiler fuels which increases the fuel cost because of the boiler stoppage due to
higher flue gas SPM values ( more than 150 ppm )
Goal statement:
To reduce the flue gas SPM value mean from 156 ppm to < 100ppm by Jun’2010
Scope
In Scope: This project scope starts from combustion of fuel, fly ash filtration, ash
handling and ash disposal with Rice husk as fuel
Out Scope: Other seasonal fuel usage like Groundnut shell, Saw dust etc can be
treated as out of scope for this project
DMAIC 13

14. Define - Step B: Develop Team Charter
Impact of problem
• Many internal complaints from dipping and other areas.
• Fly ash compliant received from Manali Municipality on 03.11.09
• Threat of biomass boiler operation due to the external complaints
• Hence the reduction of flue gas SPM value of biomass boiler is inevitable
Linkage to business goals
Additional fuel cost due to biomass boiler stoppage – running of oil fired boilers Rs 45 Lacs per month:
COC impact 4.2 Rs/Kg increase
Standard technical solution for the fly ash carry over through the chimney
Installation of Electro static precipitator ( ESP) instead of bag filter technology.
But ESP technology is very costly Rs 2.0 crores. Normally ESP will be used in power plant
high pressure boilers. Also the installation time is high.
Hence it is decided to solve this problem with the bag filter technology itself.
Quantitative deliverables Qualitative deliverables
Fuel and R & M cost savings Adhering the Pollution Control Board norms Suspended
Rs 30 Lac/annum Particulate Matter( SPM ) less than 150 ppm
( stoppage of boiler due to Ensure the health of Employee’s & near by residents
fly ash complaints) by fly ash free environment
14

15. Define - Step B: Develop Team Charter
MILESTONE CHART
DMAIC 15

16. Define - Step B: Develop Team Charter
Roles & Responsibilities : ( ARMI Tool )
DMAIC 16

17. Define - Step C: Define Process Map
HIGH LEVEL PROCESS MAPPING
SIPOC
Supplier Input Process Output Customer
Fuel Vendors Rice Husk, Steam Steam at 16 Poly, Spg, Engg
WTP kg/cm2 pressure Plastics poly,
Water Generation
RO Plant & BR&D
Challenge
Elimination of fly ash scattering with rice husk as fuel
So far the OEM ( M/s Thermax ) has not suggested the right solution for this.
Achieving Zero fly ash complaint with the available bag filter technology
will be the major challenge.
DMAIC 17

18. Measure - Step 1: Select CTQ Characteristics
Biomass steam generation process
Steam to plant
Flue
Steam flow meter Induced gas
draft fan Chimney
Direct
heating
Process
No recovery
Fuel measurement
Indirect
heating
Screw conveyor Fuel
Furnace 600-650 degc feeding
Conden Cold water from WTP
sate 32 deg c
90 degc
In bed coil
water circulation
Feed water Fludized bed
tank Forced draft fan
Feed water Blow Atmospheric
72 degc down air
Feed water
to
pump ETP
DMAIC 18

19. Measure - Step 1: Select CTQ Characteristics
CTQ Characteristics : Flue gas SPM value
Data Type : Continuous data
Operational Definition
Flue gas SPM value of biomass steam boiler
SPM value is defined as the suspended particulate matter in the flue gas which
is emitted through the chimney. This value is recorded in the centre of the
chimney.
Measurement Source
SPM on line meter- Forbes marshal make codel
UOM : PPM or mg/Nm3
DMAIC 19

20. Measure - Step 2: Define Performance standards
DMAIC 20

21. Measure - Step 3: Measurement System Analysis
Measurement System Analysis- Steam flow
MSA is carried out since, biomass steam boiler SPM measurement system is new to
SRF.
Gage R&R (ANOVA) for Measurement
Reported by :
SPM value
M .S U RE S H & P .S U RE S H BA BU
G age name: O n line S P M meter Tolerance:
M isc:
Components of Variation Measurement by Part
100 % Contribution
% Study Var 150
Percent
50 100
50
0
Gage R&R Repeat Reprod Part-to-Part 1 2 3 4 5 6 7 8 9 10
Part
R Chart by Operator
Measurement by Operator
1 2 3
Sample Range
2
150
1
_ 100
UCL=0.257
R=0.1
0 LCL=0
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
50
Part 1 2 3
Operator
Xbar Chart by Operator
1 2 3 Part * Operator Interaction
Sample Mean
150 O perator
_
_ 150 1
Average
LCL=114.0
UCL=114.2
X=114.1 2
100 3
100
50
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
50
Part 1 2 3 4 5 6 7 8 9 10
Part
DMAIC 21

22. Measure - Step 3: Measurement System Analysis
MSA- GAGE R & R Work sheet
SPM
value
MSA
passed
DMAIC 22

23. Analyze - Step 4: Establish Process Capability
Run Chart of Flue gas SPM Bag filter
bypassed during
Bag Run Chart of SPM value in PPM startup
210 filter
200
bypass
due to
190
solenoid
180 valve
SPM Value
170 failure
160
150
140
130
120
1 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150
Observation
Number of runs about median: 55 Number of runs up or down: 91
Expected number of runs: 78.4 Expected number of runs: 103.7
Longest run about median: 11 Longest run up or down: 5
A pprox P-Value for C lustering: 0.000 A pprox P-Value for Trends: 0.008
A pprox P-Value for Mixtures: 1.000 A pprox P-Value for O scillation: 0.992
Data were not stable since Clustering ( 0.000) and Trends ( 0.008) P value is less than 0.05
Two special causes identified; 1. Bag filter by passed due to solenoid valve failure
2. Bag filter bypassed during Boiler cold startup
DMAIC 23

24. Analyze - Step 4: Establish Process Capability
Run chart of Post identified special causes
Data is Stable
DMAIC 24

25. Analyze - Step 4: Establish Process Capability
Normality test
Summary of SPM Value in PPM
A nderson-D arling N ormality T est
A -S quared 2.19
P -V alue < 0.005
M ean 125.94
S tD ev 7.74
V ariance 59.85
S kew ness -0.277810
K urtosis -0.193905
N 121
M inimum 105.00
1st Q uartile 121.00
M edian 126.00
3rd Q uartile 132.00
105.0 112.5 120.0 127.5 135.0 142.5 M aximum 145.00
95% C onfidence Interv al for M ean
124.55 127.33
95% C onfidence Interv al for M edian
126.00 126.00
95% C onfidence Interv al for S tD ev
9 5 % C onfidence Inter v als
6.87 8.86
Mean
Median
124.5 125.0 125.5 126.0 126.5 127.0 127.5
Since the Anderson – Darling Normality test p-value is < 0.05 , Data is Non-Normal
DMAIC 25

26. Analyze - Step 4: Establish Process Capability
Process Capability
DMAIC 26

27. Analyze - Step 5: Define Performance Objectives
Bench mark( Z Bench ) : (-)2.37 Sigma
Z LSL : 10.38 Sigma
Z USL : (-) 4.85 Sigma
DMAIC 27

28. Analyze - Step 6: Identify Variation sources
Cause & Effect Diagram – Low Evaporation Ratio
DMAIC 28

29. Improve - Step 7: Screen Potential Causes
Control Impact Matrix
Prioritizing the Potential Causes
Actions planned for In control, High & Medium Impact causes
DMAIC 29

30. Improve - Step 7: Screen Potential Causes
Validation of causes
Cause 1. High steam pressure Cause 2. Excess blow down
Scatterplot of Evaporation ratio vs Steam pressure in Kg/cm2 Scatterplot of Evaporation ratio vs Blowdown TDS
3.6 3.50
3.5 3.45
Evaporation ratio
3.40
3.4
3.35
ER
3.3
3.30
3.2
3.25
3.1
3.20
15.5 15.6 15.7 15.8 15.9 16.0 16.1 16.2 2000 3000 4000 5000 6000
Steam pressure in Kg/cm2 - Data from Apr 09 to June 09 TDS - Data from 01 Apr 09 to 15 May 09
Negative relation between Evaporation ratio
No relation between Evaporation ratio and Blow down water TDS.
and steam pressure Current TDS of blow down water : 5983 ppm
Max. achievable TDS : 1000 ppm
DMAIC 30

31. Improve - Step 7: Screen Potential Causes
Validation of causes
Cause 3. High water level in boiler drum Cause 4. Excess air in flue gas
Scatterplot of Evaporation ratio vs Boiler drum water level in % Scatterplot of Evaporation ratio vs Oxygen content
3.6
3.5
3.5
3.4
Evaporation ratio
Evaporation ratio
3.4
3.3
3.3
3.2
3.2
3.1 3.1
48.5 49.0 49.5 50.0 50.5 10 11 12 13 14 15 16 17
Boiler drum water level in %- Data from A pr 09 to Jun 09 Oxygen content in % - Data from May 09 to Jun 09
No relation between Evaporation ratio and
water level in boiler drum Negative relation between Evaporation ratio
and oxygen content in flue gas
Current oxygen content of flue gas : 13.7 %
Max. achievable oxygen content : 10%
DMAIC 31

32. Improve - Step 7: Screen Potential Causes
Relation between Response (Y) & Factors ( Xs)
Evaporation ratio ( Y ) = F( X1,X2,X3,X4)
Where,
X1 = Old husk usage
X2 = Breakdown of boiler, Nos
X3 = Blow down water TDS in ppm
X4 = Oxygen content in flue gas in %
Maximize Y = ( Eliminate X1, Eliminate X2 , X3 , X4 )
X1 & X2 are special causes ; solutions needs to be arrived
X3 & X4 are common causes ; solutions needs to be arrived
DMAIC 32

33. Improve - Step 8: Discover Variable Relationships
SPECIAL CAUSE No. 1: Old husk usage
Operational Definition
OLD HUSK : The husk which was stored for a long time.
Gross Calorific value : Calorific value is the measurement of the heat produced during
the combustion of fuel. Unit of measurement Kcal/kg
Validation of cause – old husk usage Gross Calorific value decreases
BETTER Husk Gross calorific value with time
drastically after two months of
3400
storage time due to natural
biological degradation
3300
Conclusion : Husk aging > 2
GCV in Kcal/kg
3200
months should not be used for
3100 the Biomass process
3000
2900
2800
New husk 2 months old 4 months old 6 months old >6 months old
husk husk husk husk
Different ageing husk samples sent to Gross calorific value
lab for checking the Gross Calorific decreases
Value ( Proximate Analysis) as storage time increases
DMAIC 33

34. Improve - Step 8: Discover Variable Relationships
SPECIAL CAUSE No. 1: Old husk usage
Husk
WHY 1 Why Old husk usage ? supplied by
Husk not consumed as & when received vendor
directly from
WHY 2 Why Husk not consumed as and when received ? the Rice Mill.
No storage
Min. inventory level maintained and current incoming husk used system in
vendor side
How How to correct it ?
To implement First-In-First-out (FIFO) system.
KAIZEN
Existing System Proposed System
15 days 15 days
Husk loading point storage Husk loading point storage
30 days storage
(1000 MT) Daily Usage
Daily Unloading 15 days
15 days usage
usage
DMAIC 34

35. Improve - Step 8: Discover Variable Relationships
SPECIAL CAUSE No. 2: Breakdown of boiler
Biomass Boiler - Breakdown Time Biomass Boiler - No. of Breakdowns
160 8
BETTER
BETTER
BETTER BETTER
140 7
120 6
Avg - 5 nos / month
Nos / month
Hrs / month
100 5
80 4
Each cooling and
60 Avg - 47 hrs / month 3
heating (600 deg
40 2 C) up consumes
fuel which is not
20 1 yielding steam
0 0
output
Mar-09 Apr-09 May-09 Jun-09 Jul-09 Mar-09 Apr-09 May-09 Jun-09 Jul-09
Pareto Chart of Breakdown ( Mar to Jul 09)-
Physical phenomena
22 100
20 90
18 80
No of breakdown
16 70
14
60
Percent
12
50
10
Stone accumulation & 8 40
Shell tube puncture 6 30
4 20
2 10
0 0
Stone Shell tube Screw feeder Ash deposit in
Husk jam
accumulation puncture VFD trip bed
No of B/d 14 5 1 1 1
Cumm% 63.6 86.4 90.9 95.5 100.0
35

36. Improve - Step 8: Discover Variable Relationships
SPECIAL CAUSE No. 2: Breakdown of boiler
Why Why Analysis – Stone accumulation
WHY 1 Why stone accumulation in bed ? Capex raised for Rs
Stone carryover along with husk 4.5 Lacs Capex No
J 1611
WHY 2 Why stone carryover along with husk ? Flooring area for husk storage BETTER
800
Husk stored in raw land 700
700
600
WHY 3 Why husk stored in raw land ? 500
400
Sqm
Insufficient flooring
400
300
200
HOW How to correct it ? 100
To extend the husk storage flooring area 0
Be fore Now
Existing flooring area for husk storage – 400 Sqm Extended flooring area from 400 Sqm to 700 Sqm
36

37. Improve - Step 8: Discover Variable Relationships
SPECIAL CAUSE No. 2: Breakdown of boiler
Why Why Analysis – Shell tube puncture
WHY 1 Why Shell tube puncture ? Expert Opinion:
Scale sample sent to
Local heating of shell tube and bulging Thermax for analysis.
Thermax recommended
WHY 2 Why local heating of shell tube ? DM water. This is the
Scale accumulation inside the shell tube bundles input for Thermax also.
WHY 3 Why scale accumulation ? Soft water TDS – 400 – 450 ppm
Due to soft water usage Hardness - < 5 ppm
DM water TDS < 10 ppm
HOW How to correct it ? Hardness – 0 ppm
DM water to be used in place of soft water
Bulging photo Shell tube failure location analysis
37

38. Improve - Step 8: Discover Variable Relationships
COMMON CAUSE No.1 : Excess Blow down
Blow down : When water is evaporated into steam in boiler drum,
the solids in water gets separated and settles in boiler drum
The quantity of solids in boiler drum is measured in terms of blow down TDS ( Total dissolved solids )
Blow down is the activity to release the boiler drum water to maintain the TDS value
High TDS
Excess blow down is the quantity of extra water released from the boiler. water will
This extra water will take the heat from the boiler. damage the
Sufficient boiler tubes
I-MR Chart of Blow down TDS ( Scaling &
Blow down
1500
1
corrosion )
not given
1
1
Individual Value
1250
U C L=1141
1000
_
750 X=782
500
LC L=423
1
1
1 7 13 19 25 31 37 43 49 55 61
O bser v ation fr om July 0 9 to A ug 0 9 Excess blow
1
down
480 1
U C L=440.8
Moving Range
360
240
__
120 M R=134.9
0 LC L=0
1 7 13 19 25 31 37 43 49 55 61
O bser v ation fr om July 0 9 to A ug 0 9
To improve the Mean from 782 ppm to 1000 ppm
DMAIC 38

39. Improve - Step 8: Discover Variable Relationships
Excess blow down
Blow down
is given
manually
by opening
the valve
once in a
shift.
POKA -YOKE
Problem Corrective action
Proposed
Blow down water TDS Auto blow down suggested
variations are high in place of manual blow
down
DMAIC 39

40. Improve - Step 8: Discover Variable Relationships
COMMON CAUSE No.2 : Excess air in flue gas
Combustion
Heat Heat Heat + Smoke
Co2,N2,H20 CO
O2,Co2,N2,H20
Flue
gas
Perfect Good Incomplete
combustion combustion combustion
Fuel, Air Fuel, Air Fuel, Air
H20 O2 & N2 H20 O2 & N2 H20 O2 & N2
Air fuel ratio for Rice husk : 4:1
More O2 in flue gas – More heat loss through chimney
Less O2 in flue gas – Leads to incomplete combustion
Operational Definition- Excess air in flue gas
It is the quantity of extra air available in flue gas than air fuel ratio
UOM-Oxygen content in %
Measuring instrument – Flue gas analyzer
DMAIC 40

41. Improve - Step 8: Discover Variable Relationships
Control Chart for Oxygen content – Period (May‟09 – June‟09)
More oxygen
in furnace I-M R C har t of O x yge n co nte nt i n %
1 1
16 U C L= 1 6 . 15 1
Individual Value
14 _
X= 1 3 .6 0 7
12
LC L= 1 1 .0 6 4
10 1
1 6 11 16 21 26 31 36 41 46
O b se r v a t io n fr o m 1 5 M a y t o 3 0 J u n 0 9
Less oxygen
1
4
in furnace
U C L= 3 . 1 25
M oving Range
3
2
__
1 M R = 0 .9 5 7
0 LC L= 0
1 6 11 16 21 26 31 36 41 46
O b se r v a t io n fr o m 1 5 M a y t o 3 0 J u n 0 9
To reduce the Mean from 13.6% to 10% Need to optimize the O2 content in flue gas
Planned to do Experiments to find the optimum condition
41

42. Improve - Step 8: Discover Variable Relationships
Design of Experiments- Full factorial design
Full factorial , 2 levels, 3
factors & 2 replicates
Randomized
design of
experiments
with Minitab
version 15
DMAIC 42

43. Improve - Step 9: Establish Operating Tolerances
Analyze Factorial Design
Main Effects Plot for Response - Oxygen content in %
Data Means
ID draft in furnace FD fan speed
13
12
No three way 11
Mean
interaction & No -1 1 -1 1
interaction of Fuel screw feeder speed
Factor B & C 13
with response 12 Best model
ID draft = (-1) = -1
11 mmwc,
FD fan speed = (+1)
-1 1
= 38 Hz
Screw feeder speed
Interaction Plot for Response - Oxygen content in % Cube Plot (data means) for Response - Oxygen contentHz %
= (-1) = 34 in
Data Means
-1 1 -1 1 10.55 13.85
14
ID draft
in furnace
-1
12 1
ID dr aft in fur nace
9.85 13.55
1
10
14
FD fan
speed
-1
12
FD fan speed 1
FD fan speed 10.65 12.55
10 1
Fuel screw feeder speed
11.00 13.15
Fuel scr ew feeder speed -1 -1
-1 1
ID draft in furnace
DMAIC 43

44. Improve - Step 9: Establish Operating Tolerances
Prediction of Oxygen content from the selected model
P value less than 0.05
factors are considered
for the equation by
multiplying Co efficient
value
DOE results shared with M/s
Thermax – Engg Division-
Pune. Thermax suggested
to implement the selected
model.
Best model will
give 10.03% of
Oxygen content.
DMAIC 44

45. Improve - Step 9: Establish Operating Tolerances
Implementation Schedule Communication Matrix
DMAIC 45

46. Control - Step 10: Validate Measurement system
Gage R & R study for Excess air in flue gas O2 % ( Vital “X” )
Gage R&R (ANOVA) for Measurement
Reported by : M .S uresh
G age name: E xcess air in flue gas O 2 % Tolerance:
D ate of study : 20.09.2009 M isc:
Components of Variation Measurement by Part
100 % Contribution
% Study Var
14.4
Percent
13.6
50
12.8
0
Gage R&R Repeat Reprod Part-to-Part 1 2 3 4 5 6 7 8 9 10
Part
R Chart by Operator
Measurement by Operator
1 2 3
0.10
14.4
Sample Range
13.6
0.05
_
UCL=0.0172 12.8
R=0.0067
0.00 LCL=0
1 2 3
Operator
Xbar Chart by Operator
1 2 3 Operator * Part Interaction
14.4 14.4
Operator
Sample Mean
1
_
Average
_ 2
13.6 LCL=13.681
UCL=13.695
X=13.688 13.6 3
12.8
12.8
1 2 3 4 5 6 7 8 9 10
Part
DMAIC 46

47. Control - Step 10: Validate Measurement system
MSA- GAGE R & R Work sheet
Excess
air in
flue
gas
MSA
passed
DMAIC 47

48. Control - Step 11: Determine Process Capability
Run Chart of Flue gas SPM
All Clustering, Trends, Mixtures & Oscillation p value is more than 0.05
Data is Stable
DMAIC 48

49. Control - Step 11: Determine Process Capability
Normality test
Since the Anderson – Darling Normality test p-value is 0.005 < 0.05 , Data is Non normal
DMAIC 49

50. Control - Step 11: Determine Process Capability
Process Capability
Z USL : 10.38 Sigma
Z Bench : -2.37 Sigma
Z USL : -4.85 Sigma
Process Capability of after data
Calculations Based on Weibull Distribution Model
LSL USL
P rocess D ata O v erall C apability
LS L 0 Z.B ench 3.32
T arget * Z.LS L 5.23
USL 100 Z.U S L 3.24
S am ple M ean 71.1154 P pk 1.08
S am ple N 130
E xp. O v erall P erform ance
S hape 7.32133
P P M < LS L 0.00
S cale 75.6462
PPM > USL 445.26
O bserv ed P erform ance P P M T otal 445.26
PPM < LS L 0.00
PPM > USL 0.00
PPM T otal 0.00
Z USL : 3.24 Sigma
Z Bench : 3.32 Sigma
Z USL : 5.23 Sigma
0 20 40 60 80 100 120 140
DMAIC 50

51. Nos / month
Fe
0
1
2
3
4
5
6
7
8
9
10
b-
1
M 0
ar
-1
Ap 0
r-
M 10
ay
-1
Ju 0
n-
Au 1
Ju 0
g
Au Is l-10
Before
g tw
2 e
Au nd ek
g w
3r ee
Au d k
Avg - 7 nos / month
g we
Se 4th ek
p w
Se 1s eek
p tw
2 e
Se nd ek
p w
3r ee
Se d k
After
p we
4 ek
O th
ct we
O 1st ek
ct w
2n ee
O k
ct d w
3 e
Biomass Boiler - No. of bag filter bypassed
O r d ek
ct w
4 e
DMAIC
No th ek
BETTER
v we
1s e
tw k
ee
k
Control - Step 11: Determine Process Capability
51
introduction
filter bypass
delay for bag
7 minutes time

52. Control - Step 11: Determine Process Capability
Before and after IMR chart of Excess air in flue gas
13.61
Mean
14 BETTER
Oxygen content (%)
13
12
11
10.06
10
9
Before After
Std deviation
1.2 BETTER
Oxygen content (%)
1.1
1.0 0.96
0.9
0.8
0.7
0.6
0.5 0.33
0.4
0.3
0.2
0.1
0.0
Before After
DOE- SOP
implemented
DMAIC 52

53. Control - Step 11: Determine Process Capability
Hypothesis test- Claim- Excess air in flue gas reduced
Test for Equal Variances for Before and after Oxygen content
F-Test
Test Statistic 8.32
Be P-Value 0.000
Levene's Test
Test Statistic 6.99
P-Value 0.010
Af
0.2 0.4 0.6 0.8 1.0 1.2
95% Bonferroni Confidence Intervals for StDevs
Be
Af
10 12 14 16
Data
Claim is
statistically
proved
DMAIC 53

54. Control - Step 11: Determine Process Capability
Before and after X bar-R chart of SPM value
Xbar-R Chart of SPM value before & after Mean BETTER
180
156
SPM before SPM after 1 SPM after 2 160
SPM value in ppm
200 1
140
1
120
Sample M ean
100
150 72
80
60
40
100
U C L=87.7
_
_
20
X=71.6 0
50 LC L=55.4
Before After
1 12 23 34 45 56 67 78 89 100
Sample
Std deviation BETTER
SPM before SPM after 1 SPM after 2 20 18.76
80 18
SPM value in ppm
16
60 14
Sample Range
12 10.85
U C L=50.59
10
40
8
_ 6
20 R=22.17 4
2
0 LC L=0 0
1 12 23 34 45 56 67 78 89 100 Before After
Sample
DMAIC 54

55. Control - Step 11: Determine Process Capability
Hypothesis test- Claim- SPM value reduced
Boxplot of SPM value before and after
SPM value before and after
SPM after 2
SPM before
50 75 100 125 150 175 200 225
SPM value
Claim is
statistically
proved
DMAIC 55