Dm Make Up Six Sigma

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36 J SCI IND RES VOL 67 JANUARY 2008Journal of Scientific & Industrial ResearchVol. 67, January 2008, pp. 36-42

*Author for correspondence

E-mail: [email protected]

DM make up water reduction in thermal power plants using Six Sigma

DMAIC methodology

Prabhakar Kaushik 1* and Dinesh Khanduja2

1Mechanical Engineering Deptt, N C College of Engineering, Israna, Panipat 132 1072Mechanical Engineering Deptt, National Institute of Technology, Kurukshetra 136 119

Received 11 May 2007; revised 22 October 2007; accepted 24 October 2007

Six Sigma DMAIC (define, measure, analysis, improve, control) methodology has been applied to a process industry

seeking energy conservation, taking a specific case of a thermal power plant. DM (De-mineralize) water in these plants is an

expensive input material. It has been found that 0.1% increase in DM make up water consumption increases generation cost by

Rs 82.82 lakhs per annum. In present study, implementation of Six Sigma project recommendations brought down mean make

up water from 0.90% to 0.54% of MCR (Maximum Continuous Rating), accruing with it a comprehensive energy savings of

nearly Rs 304.77 lakhs per annum.

Keywords: CTQ, DM, DMAIC, Process industry, Six Sigma

Introduction

Six Sigma (SS) methodologies improve quality and

produce large cost savings1-9. Kumar4 noted that SS has

found place primarily in manufacturing industries as a

quality tool. In process industries, no such convenience

is available. Working fluid in process industries may not

be visible and its quality is measured by pressure,

temperature and flow measurement. In manufacturing

industries, production is already operating at 1-2 sigmalevel and by applying SS methodology, it can be raised

up to 5-6 sigma levels. In process industries, there are

many sub- processes that operate even at negative sigma

level because of being secondary in nature. So in process

industries, a quantum jump in sigma value by application

of SS tools cannot be expected and it is found that the

improvement potential is maximum up to 2-3 sigma

levels.

Present work is an initiative to implement SS in a

thermal power plant (TPP).

Six Sigma Application in Thermal Power Plants – ACase Study

In TPP, optimisation of cycle make up water [De-

mineralize (DM) water] consumption process involves

substantial cost. Escalating water charges from water

supply department and cost of production of DM water

from raw water are substantial. Mostly, all gas based

TPPs are operating on one module of combined cycle

power plant, which consists of two gas turbines, two heat

recovery steam generators and a steam turbine (Fig. 1).

DM water is used for steam generation through gas based

combined cycle power plant. With in this closed cycle of

DM water, DM water make up cycle is required to

compensate for the losses incurred in water-steam cycle

due to evaporation, start up and shut down venting, valvepassing and blow downs. DM make up water enters in a

condenser at atmospheric temperature that is heated over

500°C for raising steam. Flow meter is used to measure

day cycle make up water as percentage of feed water

flow. Each 0.1% increase in cycle make up water

increases generation cost by Rs.82.82 lakhs per annum,

which includes cost of heat loss, extra water and

consumption of chemicals.

Hence, the main customer CTQ (Critical to quality)

selected for SS implementation is to conserve energy by

reducing DM makeup water requirement at TPP.

Presently, makeup water consumption at TPP is around0.9-2.0% of MCR (Maximum Continuous Rating). In

comparison, other combined cycle power plants of the

same rating have been able to achieve DM water cycle

consumption of the order of 0.5-0.7%.

Methodology

To study all possible variations of water consumption,

6 months data of cycle make up water consumption has


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KAUSHIK & KHANDUJA: SIX SIGMA DMAIC METHOD FOR THERMAL POWER PLANT 37

570°C

Flue gases

570°C

G TExhaust

H.P. Steam

H.P. Steam

Gas

VTB

VTB

GT - 2

GT - 1 HRSG - 1

HRSG - 2

L.P. Steam 5kg /cm2

200°C

76 kg / cm2

528°C

Cold Water

forCondensing

CONDENSER

HOT W ELL

Condensate

Extraction Pump

HPST

LPST L . P . S t e a m

~

Deaerator

~

~

GT Gener ator I

GT Generator II

Steam Turbine

Generator

156 MW

DM W ater

Make up

Boiler Feed Pump

ABBR. Description

GT Gas Turbine

HRSG Heat Recovery Steam GeneratorVTB Vertical Tube Boiler

H.P. S team High Pressur e Steam

L.P. S team Low Pressure Steam

HPST High Pressure Steam Turbine

LPST Low Pressure Steam Turbine

Hot

Water

to be collected. Cycle make up water consumption has

to be converted in terms of percentage of MCR of feed

water flow so that this methodology can be applied to

other power plants. As it is not possible to reduce cycle

make up water consumption to zero and minimum is

the best, LST (lower specification limit) cannot be fixed

for water consumption. Hence, only USL (upper

specification limit) of 0.7% and target value of 0.5%

are specified and selected based on water consumption

pattern existing in the best power plants around.

Implementation of Six Sigma DMAIC Methodology

A five-step improvement cycle using SS organizations

(Define, Measure, Analyse, Improve, and Control;

DMAIC) has been successfully implemented in TPP to

reduce DM make up water reduction (Fig. 2).

Fig. 1— Systematic block diagram of combined cycle power plant

Fig. 2— Flow diagram of methodology adopted


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38 J SCI IND RES VOL 67 JANUARY 2008

Define

In define phase, High level process map- a SIPOC

(Supplier, Input, Process, Output, Customer) diagram,

was drawn for cycle make up water consumption

(Fig. 3).

Measure

In cycle make up water consumption at TPP, makeup water flow is measured by a flow meter. To perform

Gauge R&R study9 on this process, another flow meter

of tested accuracy and characteristics needs to put in

series to the installed flow meter. Two persons (operators

in shift) were needed to perform this experiment. Sample

size was 10 and two readings were taken on each sample,

thereby making a total of 40 readings. From the results

of Gauge R & R study, repeatability and reproducibility

Suppl ier Input Process O utput Custome r

DMPlant

Make Up W aterConsumption

Data

Operationand

Maintenancepractices

Reduction inMake Up

WaterConsumption

ThermalPower

Management

CustomerSatisfaction &Relationship

6 SigmaMethodology

Thinking

Flow

comes out to be 2.75% and 0.00% and put the percentage

study variation to be 2.75%, which is less than 10%,

indicating that flow meter was correct.

Analyse

Data is analysed and causes of problem are

discovered4 using following tools:

a) Run Chart

Run chart was drawn from data collected for day cycle

make up water from TPP measured through flow meter.

From the results found using Minitab, P-values (Fig. 4)

for clustering (0.51045), trend (0.36191), oscillation

(0.63809) and mixtures (0.48955) come out to be more

than the significance level (0.05), indicating not any

special cause of variation in data.

Fig. 3— High-level process map for cycle make up water consumption

Fig. 4— Run chart of make up water before

M a k e u p w a t e r b e f o r e i n % a g e

Observation


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b) Process Capability analysis

Process capability analysis was performed using

Minitab to draw curve for cycle make up water from

TPP measured through flow meter (Fig. 5). Z- bench

sigma value of process was found to be -0.75 and existing

DPMO level of the process comes out to be 774435.70,

which is remarkably high and shows that there are a lot

of opportunities for improvement in the process.

Passing of Drain & vent valves

Leakages from HP/LP pipelines

flanges & piping s

Improper Adjustment ofS WAS Sampling Valves

Vaccum pump overflow

Passing due to under sizing of actuators

Late closing ofDrain & VentValves during Boiler Startup Sampling Valve s remainingopen after collection of samples

MAN EQUIPMENT

M ETHOD MATERIAL

MORE DMCYCLE

MAKE UP Sample drains remained opened Passing of valves due to improper during Shutdown boiler limit switch setting Frequency of boiler Longer running with boiler tubehydraulic tests Leakage Higher no. of sample Blow down opening for Silicacollection in SWAS & conductivity test

Tube Leakages

Gland Leakages from

pump s

c) Fish-bone Diagram

Using expert experience and critical analysis of actual

combined cycle at site, a fish bone diagram drawn

(Fig. 6) to find causes of more DM water consumption

during combined cycle.

d) Bar Chart

Actual DM water wastage from different points was

measured or approximated where no measurement was

Fig. 5— Process capability analysis of make up water before implementing

DMAIC methodology

Fig. 6— Fishbone diagram


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Table 1—Action Plan (Improve and Control Phase)

Recommendation proposed Status

1 All lab analysts to be individually interacted to emphasize theimportance of closure of SWAS valves after sample collection.

Implemented

2 Six month periodic training cum awareness program for lab analysts to

be conducted to make them aware of the importance of DM water loss.

First program

already

conducted

3 Instructions to be pasted on SWAS panel for closure of sample valve’s

each time after sample collection.Im lemented

Instructions

pasted

4 Operation staff to be instructed to cross check from time to time the

position of SWAS sampling valves in their routine rounds

Implemented

Instructions

being followed

5 As an improvement measure, the frequency of blow down opening to

be changed from weekly to fortnightly

Implemented

6 To avoid the loss of DM water due to vaccum pump overflow,

solenoid makeup valves of both the seal water tanks to be adjusted

properly for both low and high level settings.

Implemented

7 Q uarterly checking of solenoid valves of both seal water tanks to be

carried out.

Implemented

8 To detect the problem of seal water tank overflow at the earliest, in the

log sheet of the operator, the daily checking of seal water tanks to be

included.

Implemented

Included in thelog sheet

9 The leakages identified from HP/LP pipelines, valve passing to be

attended during next shutdown.

To be

implemented

10 The glands of all the pumps with excessive leakages to be tightened

optimally.

Implemente d

11 A schedule to be prepared to check/tighten (if required) the glands of

all the pumps fortnightly.

Implemented

12 For on line sealing of HP steam leakages, annual maintenance contract

to be awarded

To be

implemented

identified problem from analysis phase were tackled and

shut out in control phase (Table 1).

Results

Cycle make up water consumption was 0.9% MCR,

which is equivalent to Rs 745 lakhs (Rs.82.82×0.9%)

per annum (Appendix I). Application of project

recommendation brought up the sigma level to 1.63 with

DPMO level of 51389.17 (an improvement of

723046.53) and mean of the process reduced to

0.54066% (an improvement of 0.368% mean), which is

equivalent to monitory saving of Rs 304.77 lakhs per

annum (Fig. 8). A few more agreed recommendations

are still to be implemented during plant shutdown.


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42 J SCI IND RES VOL 67 JANUARY 2008

Estimated saving from the project after implementation

of all recommendations is expected to be Rs 331.2 lakhs

per annum with mean make up water expected to come

down (< 0.5%), which is substantial for any organization.

Conclusions

Study proves that firms that successfully implementSix Sigma perform better in virtually every business

category, including return on scales, return on

investment, employment growth and stock value growth.

Higher consumption of DM water is found to be a big

problem in a thermal power plant. The causes for more

DM water consumption are SWAS, problem of valve

passing, vacuum pump overflow etc. SWAS makes a

big impact having 33% contribution for DM water

consumption. Further, some actions are recommended

to reduce the consumption of DM water. Application of

Six Sigma project recommendations brought up the

sigma level to 1.63. Estimated saving from the projectafter implementation of all recommendations is expected

to be around Rs 331.2 lakhs per annum with mean make

up water is expected to come down below 0.5%, which

is substantial for any organization.

References

1 Coronado R & Antony J, Critical success factors for the

implementation of six sigma projects in organization, TQM

Mag, 14 (2002) 92-99.

2 Henderson K M & Evans J R, Successful implementation of

Six Sigma: benchmarking: general electric company,

Benchmarking Int J, 7 (2000) 260-282.3 Kapur K C & Feng Q, Integrated optimisation models and

strategies for the improvement of the Six Sigma process, Int J

Six Sigma and Comp adv, 1 (2005) 210-228.

4 Kumar P, Six Sigma in manufacturing, Prod J , 43 (2002) 196-

202.

5 Mahanti R & Antony J, Confluence of Six Sigma simulation

and software development, Manag Aud J , 20 (2005) 739-762.

6 Mathew H, Barth B & Sears B, Leveraging Six Sigma discipline

to drive improvement, Int J Six Sigma Comp Adv, 1 (2005)

121-133.

7 Pandey P S, Neuman R & Cavanagh R R, The Six Sigma Way:

How GE, Motorola and Other Top Companies are Honing their

Performance (McGraw Hill, New York) 2000.

8 Park S H, Six Sigma for productivity improvement: Korean

business corporations, Prod J , 43 (2002) 173-183.

9 Raisinghani M S, Ette H, Pierce R, Cannon G & Dariply P,

Six Sigma: concepts, tools, and applications, Ind Manag Data

Sys, 105 (2005) 491-505.

Appendix-1

Cost calculations of loss on account of 0.1% make up water

Loss due to make up water consumption

Water is heated in boiler from 27°C at atmosphere pressure to superheated steam at 528°C and 76kg/cm2

Heat loss

Enthalpy of water at 27°C (atmosphere pressure) = 113.25 KJ/kg

Enthalpy of superheated steam at 528°C and 76kg/cm2 = 3472.74 KJ/kg

Loss in enthalpy = 3472.74 -113.25 = 3459.49 KJ/kg = (3459.49 × 1000) / 4.18 Kcal/m3 = 827629.1866 Kcal/m3

Equivalent loss in power = 827629.1866 / 1965 = 421.185 KWh/m3

(Considering Heat Rate as 1965 Kcal/ KWh for combined cycle)

Equivalent loss in monetary term = Rs 4.00 × 421.185 = Rs 1684.74 per m 3

(Considering Rs. 4.00 per unit (KWh))

Cost of DM water = Rs 22.00 per m 3

Total loss on account of make up water =Heat loss + water loss = Rs 1684.74 per m 3 + Rs 22.00 per m3 = Rs 1706.741 per

m3

Losses on account of 0.1% make up water

Total flow in boiler per annum = [(231(HP) + 46 (LP)) × 2 (Boiler)] ×24 h ×365 days = 4853040 m3

Water quantity for 0.1% make up = (0.1 × 4853040)/ 100 = 4853.04 m3 per annum

Therefore, loss on account of 0.1% make up water = 4853.04 × Rs 1706.74 = Rs 8282882.343 = Rs 82.82 lakhs approx per

annum

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