WQD2011 – BREAKTHROUGH PROCESS IMPROVEMENT – GOLD WINNER – SRF Overseas Ltd - To reduce the flue gas SPM value of Biomass boiler

1

To reduce the flue gas SPM value

of Biomass boiler

SIX SIGMA BLACK BELT

PROJECT

• Technical Textiles Business - Manali

Team Leader : M. Suresh ( Six Sigma Black belt )

Team Members : P. Sureshbabu

A.Narayanan

G. Ramakrishnan

R.Balakumar

2

CPB, 30%

PFB, 14%

TTB, 56%

Revenue by Business Segment

# Inc. SRF Overseas

•Acquisition of businesses of SRF Polymers Ltd. by SRF Ltd. effective from Jan 1, 2009

1 TCF and BF

2 Refrigerants & N6 Segment

Belting Fabrics

Tyre Cord Fabrics in Nylon 6 TCF

Global Position

SRF Group

Gross Turnover: INR 22,792 Mn#

Technical Textiles

Business (TTB)

Tyrecord,

Belting ,

Coated Fabrics &

Industrial Yarn

Packaging Films

(PFB)

Bi-axially Oriented Polyester

film

Chemical & Polymer

Business (CPB) Refrigerants,

Chloromethanes,

Fluorospecialities

Nylon & other Engineering

plastics

Domestic

Leader*

Domestic

Leader*

2

2

3

Nylon Tyre cord used as reinforcement in Tyres

Yarn Greige Fabric Dipped Fabric

SRF product applications

Coated Fabrics Belting Fabrics

A] Technical Textiles

4

SRF product applications

B] Packaging Films

Refrigerant Gases

Chloromethanes & Fluorospecialities

C] Chemicals

5

Manali,

Tamil Nadu

Gummidipoondi,

Tamil Nadu

Dubai, UAE

Gwalior, Madhya

Pradesh

Trichy,

Tamil Nadu

Bhiwadi,

Rajasthan

Kashipur,

Uttaranchal

Indore,

Madhya Pradesh Corporate Office, Gurgaon, Haryana

SRF Group - Locations

Employees 3000 Sites = 9

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

7

Theme selected from BM themes - APC 2009-10

Define - Step A: Identify Project CTQ‟s

Source of Project idea – Internal problems DMAIC

8

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

PROJECT CTQ:


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.

DMAIC

Flue gas SPM value should not cross 150 ppm – Pollution Control Board.

Biomass steam boiler should run continuously – Internal customers.

9

Steam cost in Rs/MT

1960

845

0

500

1000

1500

2000

2500

Oil fired boiler Biomass boiler

Ste

am c

ost

Rs/

MT 57 % Reduction

BACK GROUND :

Rice husk

Biomass boiler

• 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.

By reducing the fuel cost with alternate fuel for steam generation - Solid fuel (Rice Husk)

Rice husk is fired in biomass

steam boiler for steam

generation

BETTER


DMAIC

Fuels used in Biomass boiler : 1. Coal - 100%

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

10

Biomass boiler SPM value trend

100

50

75

100

125

150

175

200

225

250

Mar-0

7

Apr-07

May-0

7

Jun-07

Jul-07

Dec-07

Feb-08

Apr-08

May-0

8

Jun-08

Jul-08

Sep-08

Jan-09

Mar-0

9

Apr-09

May-0

9

Jun-09

Jul-09

Aug-09

Sep-09

Oct-0

9

Nov-09

Target

SP

M v

alue

in P

PM

Business Case:

Define - Step B: Develop Team Charter

DMAIC

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.

TNPCB restricted the usage of coal since Manali falls in red

zone area. So 100% rice husk started using in biomass

boiler from Mar 09

BETTER

100% coal usage & 50% rice husk and

50% coal usage as fuel combinations

Fly ash complaints

increased after using 100%

rice husk

Avg 100 PPM

Target- 0

THEME: REDUCE THE FLUE GAS SPM VALUE FROM 156 TO < 100 ppm-Target –Jun 2010

11

On line Stack monitoring system ( SPM ) introduction in Biomass boiler and heater

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

Data trend

in SRF

local computer

Computer

Data transfer

through internet

Computer

TNPCB server

in Guindy


12

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.


13


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

Scope

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

DMAIC

14

Impact of problem

Quantitative deliverables Fuel and R & M cost savings

Rs 30 Lac/annum

( stoppage of boiler due to

fly ash complaints)

Adhering the Pollution Control Board norms Suspended

Particulate Matter( SPM ) less than 150 ppm

Ensure the health of Employee’s & near by residents

by fly ash free environment

Qualitative deliverables

• 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

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.

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


15

MILESTONE CHART


DMAIC

16

Roles & Responsibilities : ( ARMI Tool )


DMAIC

17

Supplier Input Process Output Customer

SIPOC

Fuel Vendors

WTP

Rice Husk,

Water

Steam

Generation

Steam at 16

kg/cm2 pressure

Poly, Spg, Engg

Plastics poly,

RO Plant & BR&D

Challenge

Define - Step C: Define Process Map

HIGH LEVEL PROCESS MAPPING

DMAIC

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.

18

Pro

ce

ss

Chimney

Feed water pump

Steam to plant

Forced draft fan

Furnace 600-650 degc

In bed coil water circulation

Induced draft fan

Screw conveyor Fuel feeding

Fludized bed

Atmospheric air

Blow

down

to

ETP

Direct heating

Indirect heating

Cold water from WTP

32 deg c

Conden

sate

90 degc

Feed water

72 degc

No recovery

Flue

gas Steam flow meter

Fuel measurement

Biomass steam generation process

Feed water tank

Measure - Step 1: Select CTQ Characteristics

DMAIC

19

Flue gas SPM value of biomass steam boiler

Operational Definition

Measurement Source

Measure - Step 1: Select CTQ Characteristics

CTQ Characteristics : Flue gas SPM value

Data Type : Continuous data

DMAIC

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.

UOM : PPM or mg/Nm3

SPM on line meter- Forbes marshal make codel

20

Measure - Step 2: Define Performance standards

DMAIC

21

Part-to-PartReprodRepeatGage R&R

100

50

0

Perc

ent

% Contribution

% Study Var

10 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 1

2

1

0

Part

Sam

ple

Range

_R=0.1UCL=0.257LCL=0

1 2 3

10 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 110 9 8 7 6 5 4 3 2 1

150

100

50

Part

Sam

ple

Mean

__X=114.1UCL=114.2LCL=114.0

1 2 3

10987654321

150

100

50

Part

321

150

100

50

Operator

10987654321

150

100

50

Part

Avera

ge

1

2

3

Operator

Gage name: O n line SPM meter

Reported by : M.SURESH & P.SURESH BA BU

Tolerance:

M isc:

Components of Variation

R Chart by Operator

Xbar Chart by Operator

Measurement by Part

Measurement by Operator

Part * Operator Interaction

Gage R&R (ANOVA) for Measurement

Measurement System Analysis- Steam flow

MSA is carried out since, biomass steam boiler SPM measurement system is new to

SRF.

SPM value

Measure - Step 3: Measurement System Analysis

DMAIC

22

MSA- GAGE R & R Work sheet

Measure - Step 3: Measurement System Analysis

SPM

value

MSA

passed

DMAIC

23

1501401301201101009080706050403020101

210

200

190

180

170

160

150

140

130

120

Observation

SPM

Va

lue

Number of runs about median: 55

Expected number of runs: 78.4

Longest run about median: 11

Approx P-Value for Clustering: 0.000

Approx P-Value for Mixtures: 1.000

Number of runs up or down: 91

Expected number of runs: 103.7

Longest run up or down: 5

Approx P-Value for Trends: 0.008

Approx P-Value for Oscillation: 0.992

Run Chart of SPM value in PPM

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

Run Chart of Flue gas SPM

Analyze - Step 4: Establish Process Capability

Bag filter bypassed during

startup

Bag filter

bypass due to

solenoid valve

failure

DMAIC

24

Data is Stable

Run chart of Post identified special causes


DMAIC

25

Since the Anderson – Darling Normality test p-value is < 0.05 , Data is Non-Normal

Normality test


DMAIC

142.5135.0127.5120.0112.5105.0

Median

Mean

127.5127.0126.5126.0125.5125.0124.5

1st Q uartile 121.00

Median 126.00

3rd Q uartile 132.00

Maximum 145.00

124.55 127.33

126.00 126.00

6.87 8.86

A -Squared 2.19

P-V alue < 0.005

Mean 125.94

StDev 7.74

V ariance 59.85

Skewness -0.277810

Kurtosis -0.193905

N 121

Minimum 105.00

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% C onfidence Interv al for StDev

95% Confidence Intervals

Summary of SPM Value in PPM

26

Process Capability


DMAIC

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

28

Cause & Effect Diagram – Low Evaporation Ratio

Analyze - Step 6: Identify Variation sources

DMAIC

29

Actions planned for In control, High & Medium Impact causes

Control Impact Matrix

Prioritizing the Potential Causes

Improve - Step 7: Screen Potential Causes

DMAIC

30

Cause 1. High steam pressure

No relation between Evaporation ratio

and steam pressure

16.216.116.015.915.815.715.615.5

3.6

3.5

3.4

3.3

3.2

3.1

Steam pressure in Kg/cm2 - Data from Apr 09 to June 09

Ev

ap

ora

tio

n r

ati

o

Scatterplot of Evaporation ratio vs Steam pressure in Kg/cm2

60005000400030002000

3.50

3.45

3.40

3.35

3.30

3.25

3.20

TDS - Data from 01 Apr 09 to 15 May 09

ER

Scatterplot of Evaporation ratio vs Blowdown TDS

Cause 2. Excess blow down

Negative relation between Evaporation ratio

and Blow down water TDS. Current TDS of blow down water : 5983 ppm

Max. achievable TDS : 1000 ppm

Validation of causes


DMAIC

31

Cause 3. High water level in boiler drum

No relation between Evaporation ratio and

water level in boiler drum

50.550.049.549.048.5

3.6

3.5

3.4

3.3

3.2

3.1

Boiler drum water level in %- Data from Apr 09 to Jun 09

Eva

po

rati

on

ra

tio

Scatterplot of Evaporation ratio vs Boiler drum water level in %

1716151413121110

3.5

3.4

3.3

3.2

3.1

Oxygen content in % - Data from May 09 to Jun 09

Ev

ap

ora

tio

n r

ati

o

Scatterplot of Evaporation ratio vs Oxygen content

Cause 4. Excess air in flue gas

Negative relation between Evaporation ratio

and oxygen content in flue gas

Current oxygen content of flue gas : 13.7 %

Max. achievable oxygen content : 10%

Validation of causes


DMAIC

32

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 %

X1 & X2 are special causes ; solutions needs to be arrived

X3 & X4 are common causes ; solutions needs to be arrived

Relation between Response (Y) & Factors ( Xs)

Maximize Y = ( Eliminate X1, Eliminate X2 , X3 , X4 )


DMAIC

33

Validation of cause – old husk usage

Different ageing husk samples sent to

lab for checking the Gross Calorific

Value ( Proximate Analysis)

Gross calorific value

decreases

as storage time increases

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

SPECIAL CAUSE No. 1: Old husk usage

Husk Gross calorific value with time

2800

2900

3000

3100

3200

3300

3400

New husk 2 months old

husk

4 months old

husk

6 months old

husk

>6 months old

husk

GC

V i

n K

cal/

kg

Gross Calorific value decreases

drastically after two months of

storage time due to natural

biological degradation

Conclusion : Husk aging > 2

months should not be used for

the Biomass process

BETTER

Improve - Step 8: Discover Variable Relationships

DMAIC

34

15 days

storage

15 days

storage

WHY 1 Why Old husk usage ? Husk not consumed as & when received

WHY 2 Why Husk not consumed as and when received ? Min. inventory level maintained and current incoming husk used

How How to correct it ? To implement First-In-First-out (FIFO) system.

Existing System Proposed System

Husk loading point

30 days storage

(1000 MT)

Husk supplied by

vendor directly from the Rice Mill. No storage system in

vendor side

KAIZEN

SPECIAL CAUSE No. 1: Old husk usage

Husk loading point

15 days

usage

15 days

usage

Daily Usage

Daily Unloading


DMAIC

35

Pareto Chart of Breakdown ( Mar to Jul 09)-

Physical phenomena

0

2

4

6

8

10

12

14

16

18

20

22

No

of

bre

akd

ow

n

0

10

20

30

40

50

60

70

80

90

100

Per

cen

t

No of B/d 14 5 1 1 1

Cumm% 63.6 86.4 90.9 95.5 100.0

Stone

accumulation

Shell tube

puncture

Screw feeder

VFD trip

Ash deposit in

bedHusk jam

Biomass Boiler - No. of Breakdowns

0

1

2

3

4

5

6

7

8

Mar-09 Apr-09 May-09 Jun-09 Jul-09

No

s /

mo

nth

Avg - 5 nos / month

BETTER

Stone accumulation &

Shell tube puncture

Biomass Boiler - Breakdown Time

0

20

40

60

80

100

120

140

160

Mar-09 Apr-09 May-09 Jun-09 Jul-09

Hrs

/ m

on

th

Avg - 47 hrs / month

BETTER

Each cooling and heating (600 deg C) up consumes fuel which is not yielding steam

output

SPECIAL CAUSE No. 2: Breakdown of boiler

BETTER BETTER


DMAIC

36

WHY 1 Why stone accumulation in bed ? Stone carryover along with husk

WHY 2 Why stone carryover along with husk ?

Husk stored in raw land

WHY 3 Why husk stored in raw land ? Insufficient flooring

HOW How to correct it ? To extend the husk storage flooring area

Existing flooring area for husk storage – 400 Sqm

Why Why Analysis – Stone accumulation


Extended flooring area from 400 Sqm to 700 Sqm

Flooring area for husk storage

400

700

0

100

200

300

400

500

600

700

800

Before Now

Sq

m

BETTER

Capex raised for Rs

4.5 Lacs Capex No

J 1611


DMAIC

37

WHY 1 Why Shell tube puncture ? Local heating of shell tube and bulging

WHY 2 Why local heating of shell tube ? Scale accumulation inside the shell tube bundles

WHY 3 Why scale accumulation ? Due to soft water usage

HOW How to correct it ? DM water to be used in place of soft water

Bulging photo

Why Why Analysis – Shell tube puncture

Soft water TDS – 400 – 450 ppm Hardness - < 5 ppm DM water TDS < 10 ppm Hardness – 0 ppm Shell tube failure location analysis


Expert Opinion: Scale sample sent to

Thermax for analysis.

Thermax recommended

DM water. This is the

input for Thermax also.


DMAIC

38

61554943373125191371

1500

1250

1000

750

500

Observation from July 09 to A ug 09

Indi

vidu

al V

alue

_X=782

UC L=1141

LC L=423

61554943373125191371

480

360

240

120

0

Observation from July 09 to A ug 09

Mov

ing

Ran

ge

__MR=134.9

UC L=440.8

LC L=0

11

1

1

1

1

1

I-MR Chart of Blow down TDS

Excess blow

down

To improve the Mean from 782 ppm to 1000 ppm

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

Excess blow down is the quantity of extra water released from the boiler.

This extra water will take the heat from the boiler.

High TDS water will

damage the boiler tubes ( Scaling & corrosion )

COMMON CAUSE No.1 : Excess Blow down

Sufficient

Blow down

not given


DMAIC

39

Problem Corrective action Proposed

Blow down water TDS

variations are high

Auto blow down suggested

in place of manual blow

down

POKA -YOKE

Excess blow down

Blow down is given

manually by opening the valve once in a

shift.


DMAIC

40

Perfect

combustion

Good

combustion

Incomplete

combustion

Fuel,

H20

Air

O2 & N2

Heat

Co2,N2,H20 O2,Co2,N2,H20

CO

Heat + Smoke

Fuel,

H20

Air

O2 & N2

Fuel,

H20

Air

O2 & N2

Heat

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

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

COMMON CAUSE No.2 : Excess air in flue gas

Flue

gas


DMAIC

41

Need to optimize the O2 content in flue gas

Planned to do Experiments to find the optimum condition

464136312621161161

16

14

12

10

O bse r v a t io n fr o m 1 5 M a y to 3 0 J un 0 9

In

div

idu

al

Va

lue

_X= 13.607

U C L= 16.151

LC L= 11.064

464136312621161161

4

3

2

1

0

O bse r v a t io n fr o m 1 5 M a y to 3 0 J un 0 9

Mo

vin

g R

an

ge

__M R = 0.957

U C L= 3.125

LC L= 0

1

11

1

I-MR Chart of O xygen content in %More oxygen

in furnace

Less oxygen

in furnace

To reduce the Mean from 13.6% to 10%

Control Chart for Oxygen content – Period (May‟09 – June‟09)


DMAIC

42

Design of Experiments- Full factorial design

Full factorial , 2 levels, 3

factors & 2 replicates


DMAIC

Randomized

design of

experiments

with Minitab

version 15

43

Analyze Factorial Design

1-1

13

12

11

1-1

1-1

13

12

11

ID draft in furnace

Me

an

FD fan speed

Fuel screw feeder speed

Main Effects Plot for Response - Oxygen content in %Data Means

1-1 1-1

14

12

1014

12

10

ID draft in furnace

FD fan speed


-1

1

in furnace

ID draft

-1

1

speed

FD fan

Interaction Plot for Response - Oxygen content in %Data Means

1

-1

1

-1

1-1


FD fan speed

ID draft in furnace

13.85

12.5510.65

10.55

13.55

13.1511.00

9.85

Cube Plot (data means) for Response - Oxygen content in %

No three way

interaction & No

interaction of

Factor B & C

with response Best model

ID draft = (-1) = -1

mmwc,

FD fan speed = (+1)

= 38 Hz

Screw feeder speed

= (-1) = 34 Hz

Improve - Step 9: Establish Operating Tolerances

DMAIC

44

Prediction of Oxygen content from the selected model

Best model will

give 10.03% of

Oxygen content.

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.


DMAIC

45

Implementation Schedule Communication Matrix


DMAIC

46

Control - Step 10: Validate Measurement system

Gage R & R study for Excess air in flue gas O2 % ( Vital “X” )

DMAIC

Part-to-PartReprodRepeatGage R&R

100

50

0

Perc

ent

% Contribution

% Study Var

0.10

0.05

0.00

Sam

ple

Range

_R=0.0067UCL=0.0172

LCL=0

1 2 3

14.4

13.6

12.8

Sam

ple

Mean

__X=13.688UCL=13.695LCL=13.681

1 2 3

10987654321

14.4

13.6

12.8

Part

321

14.4

13.6

12.8

Operator

10 9 8 7 6 5 4 3 2 1

14.4

13.6

12.8

Part

Avera

ge

1

2

3

Operator

Gage name: Excess air in flue gas O 2 %

Date of study : 20.09.2009

Reported by : M.Suresh

Tolerance:

M isc:

Components of Variation

R Chart by Operator

Xbar Chart by Operator

Measurement by Part

Measurement by Operator

Operator * Part Interaction

Gage R&R (ANOVA) for Measurement

47

Control - Step 10: Validate Measurement system MSA- GAGE R & R Work sheet

Excess

air in

flue

gas

MSA

passed

DMAIC

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

49

Control - Step 11: Determine Process Capability

Normality test

DMAIC

Since the Anderson – Darling Normality test p-value is 0.005 < 0.05 , Data is Non normal

50

140120100806040200

LSL USL

LSL 0

Target *

USL 100

Sample Mean 71.1154

Sample N 130

Shape 7.32133

Scale 75.6462

Process Data

Z.Bench 3.32

Z.LSL 5.23

Z.USL 3.24

Ppk 1.08

O v erall C apability

PPM < LSL 0.00

PPM > USL 0.00

PPM Total 0.00

O bserv ed Performance

PPM < LSL 0.00

PPM > USL 445.26

PPM Total 445.26

Exp. O v erall Performance

Process Capability of after dataCalculations Based on Weibull Distribution Model

Control - Step 11: Determine Process Capability Process Capability

Z USL : 3.24 Sigma

Z Bench : 3.32 Sigma

Z USL : 5.23 Sigma

DMAIC

Z USL : 10.38 Sigma

Z Bench : -2.37 Sigma

Z USL : -4.85 Sigma

51


DMAIC

Biomass Boiler - No. of bag filter bypassed

0

1

2

3

4

5

6

7

8

9

10

Feb

-10

Mar

-10

Apr-10

May

-10

Jun-1

0

Jul-10

Aug

Ist w

eek

Aug

2nd

wee

k

Aug

3rd w

eek

Aug

4th

wee

k

Sep

1st

wee

k

Sep

2nd w

eek

Sep

3rd

wee

k

Sep

4th

wee

k

Oct

1st

wee

k

Oct

2nd

wee

k

Oct

3rd

wee

k

Oct

4th

wee

k

Nov 1s

t wee

k

No

s /

mo

nth

Avg - 7 nos / month BETTER

Before

After

7 minutes time

delay for bag

filter bypass

introduction

52

Before and after IMR chart of Excess air in flue gas

Mean13.61

10.06

9

10

11

12

13

14

Before After

Oxyg

en

co

nte

nt

(%) BETTER

Std deviation

0.33

0.96

0.00.10.20.30.40.50.60.70.80.91.01.11.2

Before After

Oxyg

en

co

nte

nt

(%) BETTER

DOE- SOP

implemented


DMAIC

53

Af

Be

1.21.00.80.60.40.2

95% Bonferroni Confidence Intervals for StDevs

Af

Be

16141210

Data

Test Statistic 8.32

P-Value 0.000

Test Statistic 6.99

P-Value 0.010

F-Test

Levene's Test

Test for Equal Variances for Before and after Oxygen content

Claim is

statistically

proved

Control - Step 11: Determine Process Capability Hypothesis test- Claim- Excess air in flue gas reduced

DMAIC

54


Before and after X bar-R chart of SPM value

DMAIC

10089786756453423121

200

150

100

50

Sample

Sa

mp

le M

ea

n

__X=71.6

UC L=87.7

LC L=55.4

SPM before SPM after 1 SPM after 2

10089786756453423121

80

60

40

20

0

Sample

Sa

mp

le R

an

ge

_R=22.17

UC L=50.59

LC L=0

SPM before SPM after 1 SPM after 2

1

1

Xbar-R Chart of SPM value before & after Mean156

72

0

20

40

60

80

100

120

140

160

180

Before After

SP

M v

alu

e i

n p

pm

BETTER

Std deviation

10.85

18.76

0

2

4

6

8

10

12

14

16

18

20

Before After

SP

M v

alu

e i

n p

pm

BETTER

55

Claim is

statistically

proved

Hypothesis test- Claim- SPM value reduced


DMAIC

SPM before

SPM after 2

2252001751501251007550

SP

M v

alu

e b

efo

re

an

d a

fte

r

SPM value

Boxplot of SPM value before and after

56

3.643.573.503.433.363.293.22

7

6

5

4

3

2

1

0

Evaporation ratio- Data from 25 Sep 09 to 19 Oct 09

Freq

uenc

y

Mean 3.638

StDev 0.01434

N 25

Normal

Histogram of Evaporation ratio

Evaporation ratio-Before and after Histogram and Process capability

3.453.403.353.303.253.20

12

10

8

6

4

2

0

Evaporation ratio- Data from Apr 09 to Jun 09

Freq

uenc

y

Mean 3.323

StDev 0.05604

N 65

Normal

Histogram of Evaporation ratio

Evaportion ratio of Biomass boiler

2.80

3.00

3.20

3.40

3.60

3.80

Mar

-07

Ap

r-07

May

-07

Jun

-07

Jul-

07

Dec

-07

Feb

-08

Ap

r-08

May

-08

Jun

-08

Jul-

08

Sep

-08

Mar

-09

Ap

r-09

May

-09

Jun

-09

Jul-

09 I

wee

k

Jul-

09 II

wee

k

Jul-

09 II

I wee

k

Jul-

09 IV

wee

k

Au

g-0

9 I w

eek

Au

g-0

9 II

wee

k

Au

g-0

9 III

wee

k

Au

g-0

9 IV

wee

k

Sep

-09

I Wee

k

Sep

-09

II W

eek

Sep

-09

III W

eek

Sep

-09

IV W

eek

Oct

-09

I Wee

k

Oct

-09

II W

eek

Oct

-09

III W

eek

Ev

ap

ora

tio

n r

ati

o

Auto blow

down system-

TDS reduced

DOE and SOP

for

combustion

Boiler Thermal Efficiency

improved from 76% to 82% &

resulted the Cost savings of

Rs 43 Lacs per annum

BETTER

Early stage instabilities addressed

Special

causes

removed-

Breakdown

and old husk

usage

Inverter

drive with

–ve draft

controller

introduce

d in ID fan

3.64

3.33

3.48

New Benchmark


DMAIC

57

Standarization

No. of changes in Drawings : 02

No. of changes in Procedures : 02

No. of changes in Work Instructions : 05

No. of changes in QCPC : 07

No of changes in Process FMEA : 06

New standards: • Developed the new Bag filter manual

• Time based Bag replacement plan

Revision of existing standards:

Institutionalization

Check sheet introduced to monitor the Solenoid valve condition on daily basis

Unique design / practice

On line SPM monitoring

Control - Step 12: Implement Process Control system

58


DMAIC

Control chart of SPM Value – „Y‟

3128252219161310741

90

80

70

60

Sample

Sa

mp

le M

ea

n

__X=71.58

UC L=87.73

LC L=55.42

3128252219161310741

48

36

24

12

0

Sample

Sa

mp

le R

an

ge

_R=22.17

UC L=50.59

LC L=0

Xbar-R Chart of after 2

59


252321191715131197531

11.0

10.5

10.0

9.5

9.0

Observation from 25 Sep 09 to 19 Sep 09

Ind

ivid

ua

l V

alu

e

_X=10.056

UC L=11.098

LC L=9.014

252321191715131197531

1.2

0.9

0.6

0.3

0.0

Observation from 25 Sep 09 to 19 Sep 09

Mo

vin

g R

an

ge

__MR=0.392

UC L=1.280

LC L=0

I-MR Chart of Oxygen content in %

DMAIC

Control chart of Oxygen content in flue gas in %– Vital „X‟

60

Project path


DMAIC

TANGIBLE BENEFITS:

• Fuel cost reduction – Rs 32 Lacs per annum

• R & M cost reduction – Rs 2 Lacs per annum

• Total cost savings – Rs 34 Lacs per annum

(COST )

INTANGIBLE BENEFITS:

• Meeting the TNPCB SPM Norms

• Ensure the health of Employee‟s & near by

residents by fly ash free environment

• Daily management improved hence able to

contribute for improvement ( BM)

61


DMAIC

What went well ?

• Brain storming sessions

• Team work

• Effective usage of QC tools and Minitab

• Statistical validation of the results

What could be improved?

• Water sprinkler system in closed ash shed could not be

implemented in this project

• Furnace bottom ash transportation through trolley up to

ash storage area could not be eliminated as solutions for

the same could not be derived from this project

62


DMAIC

Key learning's:

• Flue gas parameters, O2 & Moisture contents are critical for

the selection of the bag filter media.

• Shifting of Mechanical dust collector will reduce the dust

load on bag filter

• Rice husk ash alone do not form any coating on bag surface

• These learning's were very useful for the Biomass Thermic

fluid heater.

1. These Learning's were horizontally

deployed in Biomass Thermic fluid

heater.

2. These learning's shared to TTBT

plant biomass steam boiler for

horizontal deployment. Way forward:

To study and improve the Rice husk storage and handling

system in rainy days by Feb-2011.

63

WQD2011 – BREAKTHROUGH PROCESS IMPROVEMENT – GOLD WINNER – SRF Overseas Ltd - To reduce the flue gas SPM value of Biomass boiler

Education

biomass steam boiler

ppm peak spm value

steam generation

tnpcb norm spm

step b

ppmat present avg spm

biomass boilerspm data

year biomass boilerdmaic