STUDY ON FACTORS INFLUENCING COKE RATE AND PRODUCTIVITY OF BLAST FURNACE AT BHILAI STEEL PLANT AND SUGGEST METHODS FOR

IMPROVEMENT

A Thesis SubmittedA Thesis Submitted

ToTo

CHHATISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY BHILAI (C.G)CHHATISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY BHILAI (C.G)

ForFor

The award of Degree ofThe award of Degree of

Master of Technology in Steel TechnologyMaster of Technology in Steel Technology

ByBy

VIKASH NASHINEVIKASH NASHINE

Enrolment No: AD7353Enrolment No: AD7353

Under the Guidance of

SHRI S. K. GHOSH

EX. DEPUTY GENERAL MANAGER

SAIL, BHILAI STEEL PLANT

&

VISITING PROFESSOR,CSVTU

BHILAI, CHHATTISGARH

UNIVERSITY TEACHING DEPARTMENT

CHHATTISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY

BHILAI (C.G.)

SESSION: 2010-2011

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DECLARATION BY THE CANDIDATE

I the undersigned solemnly declare that the thesis entitled

“Study on factors influencing coke rate and productivity of blast furnace at BSP and suggest methods for improvement”

Is my own project work carried out under the supervision and guidance of Shri S K Ghosh Ex. DGM, SAIL Bhilai Steel Plant &Visiting

professor CSVTU Bhilai.

Signature of Candidate

(V. Nashine)

Enrolment No: AD7353

Supervisor

SHRI S K GHOSH

EX. DEPUTY GENERAL MANAGER

SAIL, BHILAI STEEL PLANT &

Visiting Professor, CSVTU

Bhilai, Chhattisgarh

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Certificate By The Supervisor

Certified that the project work on “Study on factors influencing coke rate and

productivity of blast furnace at BSP and suggest methods for improvement” is a

bonafide work done under my guidance by V. Nashine in partial fulfillment of the

requirement for the award of degree of Master of Technology in Steel Technology

affiliated to Chhattisgarh Swami Vivekanand Technical University, Bhilai (C.G.)

To the best of my knowledge and belief the thesis,

Embodies the work of the candidate himself.

Has dully been completed.

Fulfills the requirement of the ordinance relating to the M.Tech. Degree of the university.

Is up to standard both in respect of contents and language for being referred to the examiners.

------------------------------------

SUPERVISOR

(S K Ghosh)

EX DEPUTY GENERAL MANAGER

SAIL BHILAI STEEL PLANT

& Visiting Professor, CSVTU Bhilai

-----------------------------------------------

Dr. A.K.DUBEY

REGISTRAR

CSVTU

BHILAI (C.G.)

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CERTIFICATE BY THE EXAMINER

This is to certify that the project work entitled “Study on factors

influencing coke rate and productivity of blast furnace at BSP and

suggest methods for improvement” carried out by Mr. V. Nashine

student of M .Tech. (Steel Technology) [2008-2010 batch] at Chhattisgarh

Swami Vivekananda Technical University, Bhilai (C.G.) is hereby

accepted and approved after proper evaluation as a creditable work

submitted in partial fulfillment of the requirement for awarding the degree

Master of Technology in Steel Technology from Chhattisgarh Swami

Vivekananda Technical University, Bhilai(C.G.).

It is understood that by this approval, the undersigned do not necessarily

endorse or approve any statement made, opinion expressed or conclusion

therein, but approve the report for the purpose for which it is submitted.

(Internal Examiner) (External Examiner)

DATE: DATE:

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Acknowledgement

I express my sincere thanks to the guide, Shri S.K Ghosh, Ex-DGM Bhilai Steel Plant and Visiting Professor, CSVTU, Bhilai for his excellent guidance. His invaluable suggestions will always linger in my memory.

I am grateful to Shri Shankar Dutta, GM (BF & SP’s) Bhilai Steel Plant and Shri P.K. Dwivedi DGM BF (o), for permitting me to take up the project and for moral support. They encouraged me at difficult moment of study and instilled a lot of confidence in me.

I wish to thank and acknowledge all the help rendered to me by, Shri S. Tokdar AGM BF (Opr) & Furnace incharge of BF-5, BSP, Shri Abhik Chakraborti, SM BF (Opr), Shri Manish Tiwari DM, BF(Opr)BSP, Shri Salil Jain DM BF (Opr) , Shri Bhargav & Shri Tandi from statistical section of BF, BSP and Shri Deepak Agrawal from BF (Opr) .

I also wish to express sincere thanks to the Course coordinator Shri M. L. Deshmukh and support staff of CSVTU for providing everything that was required for the successful completion of my thesis work. I would also like to thank Shri Prakash Pandey , OSD(academic), CSVTU for extending his regular support and timely help. I also take the opportunity to thank Registrar CSVTU, Dr.A.K.Dubey, Hon.Vice-chancellor CSVTU and Dr. Bimal Chandra Mal for their continuous support and encouragement.

Last but not the least I would like to thank my wife Smt.Namrata Nashine for her moral support and co-operation without which this endeavour of M.Tech is not possible for me.

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ABSTRACT

Bhilai Steel Plant is the flagship of SAIL. In the last financial year 2010-11 its production was 5.7 Million Tonnes of hot metal. The Plant is now going through a massive capacity expansion with an envisaged increase in capacity post expansion to 7.0 Million Tonnes.

BSP being an integrated steel plant, where the role of Blast furnace is very important & performance of Blast furnace is judged by two very important factors, its coke rate and productivity.

In this project work I have detailed what is coke rate and productivity in Blast furnace context, Blast furnace working, role of coke and its importance in furnace performance, Different factors which influence Blast furnace productivity & coke rate. And with the help of data analysis of one furnace, try to suggest positive & negative influence of these factors. For analysis purpose I have used regression analysis technique, which is the best way of calculating or establishing a relationship between a dependent variable and number of independent variables, theory of regression analysis is also included in brief.

As Blast furnace coke rate and productivity are affected by a number of factors out of which most important are chosen for analysis and based on this analysis suggestion is given.

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LIST OF ABBREVIATIONS

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MT Million Tones

BSP Bhilai Steel Plant

BRL Bharat Refractories Limited

BF Blast Furnace

HM Hot Metal

THM Tons of Hot metal

BLT Bell less top

RCU Rotary Charging Unit

DC Danielli Corus

CP Claudius Peters

PW Paul Wurth

HBT Hot blast temperature

CDI Coal Dust Injection

SGP Slag granulation Plant

GCP Gas Cleaning Plant

HTP High top pressure

DDHM Delay in disposing off hot metal

ASU Air separation Unit

CDPP Coal Dust Preparation Plant

HBV Hot Blast Valve

BD Back Draught

FC Fixed Carbon

Contents

Declaration by the candidate............................................................ iCertificate by the supervisor............................................................. iiCertificate by the examiners.............................................................. iiiAcknowledgement.............................................................................. ivAbstract.............................................................................................. v

Chapter Page No.

1 Introduction ……………………………………………............

1.1 Inspiration of the project

1.2 Objectives of the project

1.3 Productivity and coke rate of Blast Furnace

1.4 Blast Furnace process and role of coke

2 Literature Survey ………………………………………..........

2.1 Factors affecting coke rate and productivity of BF at BSP

2.1.1 Preparation and concentration of iron ore

2.1.2 Coke quality

2.1.3 Use of sinter

2.1.4 Hot Blast Temp.

2.1.5 Blast volume

2.1.6 High top pressure

2.1.7 Cast house practices

2.1.8 Tap hole clay

2.1.9 Not dry cost

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2.1.10 Quality of hot metal (control over chemistry)

2.1.11 slag rate

2.1.12 different charging practices

2.1.13 Use of blast additives ( oxygen, steam ,auxiliary fuel etc)

2.1.14 Decrees in break down repair and down time

3 BF of BSP and selection of BF-5 for study........................................

3.1 overview of Bhilai Blast furnaces

3.2 Coke rate and production data of Bhilai Blast furnaces

3.4 Reason for selection of Blast furnace 5

3.5 Blast furnace 5 dimension & diagrams

4 A brief overview on international standards

5 Theory of data analysis

6 Analysis Of Data..........................................................................

6.1 data analysis of BF-5

7 Suggestion based on analysis ……………….....................

8 Conclusion

9 References

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LIST OF FIGURES

Figure No Description Page No

1. Inner state of BF

2. Existence of TRZ

3. Top and bottom zone of BF

4. C-rd diagram

5.

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LIST OF TABLES

Table No Description Page No

1

2

3

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INTRODUCTION

INSPIRATION OF THE PROJECT

History of iron making in Bhilai is 50 years old. We have touched so many land marks. When we see the records of production, productivity, coke rate, quality & other parameter and compare with other units of SAIL it looks very great.

Although productivity & coke rate of Blast furnace depends upon so many inputs & other factors but comparing with world standard we have to work lot, My inspiration comes from this thought.

In this Project I am trying to find the factors which greatly affects the coke rate & Productivity in Bhilai Blast furnaces & responsible for till date achievements in this areas, and by suggestion I want to point out how we can improve in this areas and touch the highest standard.

OBJECTIVE OF THE PROJECT:-

As a ten times Prime minister trophy winners for the Best integrated steel plant in India, Bhilai has to show continuous growth in two important parameters (Coke rate & Productivity) of Blast furnaces.

In spite of improving quality of raw materials (Which affects greatly in it) there are lots of ways we can improve in these two areas. The objective of this Project is to find out the factor’s which are responsible for that and how we improve on this areas by constant & correct approach, and with the help of data analysis do it.

PRODUCTIVITY AND COKE RATE

The basic aim of BF operator is to produce hot metal with required specification and the lowest possible cost.

Coke forms the major portion (60 – 65%) of the cost of hot metal. Also, sources of metallurgical coal needed to produce coke are limited. Therefore decreasing the coke consumption has always been an important task in B.F iron making. The motivation of coke economy has led to numerous investigations into the basic understanding of the B.F process, especially in the last six decades

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and thereby to a large improvement in performance indices of the B F viz productivity & Coke rate.

A high productivity & low coke rate operation is a must to survive in today’s competitive world.

The most important criteria for measuring success in B.F. operation are “PRODUCTIVITY” and “COKE RATE” There are many indices to measure B.F. productivity and all are based on hot metal production rate.

PRODUCTIVITY BASED ON HEARTH AREA:

(Tons / m2 / day)

PRODUCTIVITY BASED ON WORKING VOLUME

(Tons / m3 / day)

PRODUCTIVITY BASED ON USEFUL VOLUME:

(Tons / m3 / day)

K I P O (Furnace volume utilization coefficient)

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= (m3 /Ton/day)

=

Since the value of hearth area & volume (useful or working) is fixed for a given B.F., the only way to increase the productivity index is to increase the daily hot metal production rate of the B F.

Production rate of a B.F. depends upon the amount and rate of carbon burnt at the tuyeres. The amount of coke burnt in a day is called the coke burning rate or coke throughput or driving rate per day.

The specific coke consumption is coke consumed for production of a ton of hot metal is termed as coke rate of the B F.

Thus =

Thus to increase production rate or productivity of a B.F. it is required to increase the rate of coke burning at tuyers and to decrease the specific coke consumption or coke rate. The coke throughput can be increased by:

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Increased oxygen supply at the tuyeres through -

Increased blast volume

Oxygenated blast

Humidified blast

High top pressure operation

Decreased volume and viscosity and increased density and surface tension of slag.

The coke rate can be decreased by:

Better raw materials

Increased blast temp

Blast additives like auxiliary fuel injectants

Since all the above measures relate either to increasing coke burning intensity or decreasing specific coke consumption, let us first understand the basics of B.F. process and the role of coke in it.

THE B.F. PROCESS AND ROLE OF COKE:-

As a result of Japanese dissection studies of quenched BFs in early 1970’s, the inner state of B.F. is revealed which is schematically represented in fig1. The most significant contribution of the studies was the evidence of the existence of a “cohesive zone” (Softening melting zone) with alternate layers of coke and fused slag & iron which plays an important role in aerodynamics & gas distribution in the furnace.

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The extensive work by Kitaev and Michard has shown that complete heat exchange takes place in a B.F. between descending solids and ascending gases. Refer to fig 2 which shows that over a considerable height in shaft a thermal reserve zone (TRZ) exists, and is evident from the temperature curve of solids and gases.

In steady state, the B.F can schematically be divided into two zones – the bottom and the top zone, as shown in fig 3 separated by the root of TRZ marked by the end of direct reduction or solution loss reaction . The bottom zone carries all the important heat consuming reactions (such as solution loss, direct reduction of Mn, Si, P and melting of slag and iron) and determines the fuel consumption of the furnace. The top zone uses the thermal potential of the gases arriving from the bottom zone to preheat the burden and chemical potential of gases to carry the indirect reduction of iron oxides.

With this summarized description, let us look at the role of coke in the process.

The coke plays a double role - the thermo chemical (i.e. to provide heat & chemical requirement of process) and the physical (i.e. facilitating the flow of gases and liquids and supporting the burden).

Thermo-chemical function of coke :

The preheated coke gets burnt with hot blast in front of the tuyeres and provides on one hand the heat required for the process and on the other hand reducing gases.

To understand the relationship between thermal & chemical function of coke,we recall that reduction of iron oxides takes place by following two reactions:

Indirect reduction – which takes place at T < 10000C

FeO + n CO Fe + CO2 + (n-1) CO + 3250 Kcal

Direct reduction – taking place at T > 10000C

FeO + C Fe + CO – 36500 Kcal

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It is clear that these two reactions are diametrically opposite in their thermal effect and reducer requirement. Indirect reduction is slightly exothermic with large reducer requirement (n = 3 to 4) because of equilibrium considerations. Where as direct reduction is highly endothermic but requires only one mole of C for reducing one mole of FeO. It is apparent therefore, that a certain combination of the two reactions will give the optimum carbon consumption for reduction of a mole of FeO to Fe.

If the carbon rate per ton of hot metal as dictated separately by thermal & chemical requirement is plotted against the degree of direct reduction

rd = (ratio of FeO reduced directly to total FeO per THM) ,we get a plot known as C-rd

diagram as shown in fig 4. It can be seen that the point of intersection of two lines, viz, O, at which both thermal and chemical requirements are satisfied, gives the optimum degree of direct reduction rd,opt and corresponding carbon rate i.e. the optimum carbon rate, Copt. Referring to C-rd

diagram, the coke economy can be brought about by the methods which either shift down the thermal requirement line (Increase in hot blast temp, elimination of raw fluxes from burden, decrease in slag rate) or shift down the chemical requirement line (By using Prepared burden, sponge iron addition etc.)

Physical function of coke:-

Coke is the only charge material which reaches up to tuyeres in solid state, so in the bosh & hearth it acts as a mechanical support to the burden.

The presence of coke in front of the tuyeres leads to formation of raceway which facilitates distribution of gases and temperature across the furnace cross section; more importantly only due to coke slits in the cohesive zone, the reducing gases are allowed to flow upwards & distribute to the cross section of stack. In short coke provide permeability for ascending gases in the descending burden.

Other functions of coke:-

Carburization of hot metal with the carbon of coke helps in lowering the melting point of iron.

The Coke also helps in reduction of various metalloids (like MnO, SiO2, P2O5, TiO2 etc.)

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CHAPTER 2

LITRATURE SURVEYA brief survey has been made on factors affecting coke rate and productivity in Bhilai Blast Furnaces are as

1. Preparation and concentration of iron ore.

2. Coke quality.

3. Use of sinter.

4. Hot blast temp.

5. Blast volume.

6. High top pressure.

7. Cast house practice.

8. Tap hole clay

9. Not dry cast

10.Quality of hot metal. (control over chemistry)

11.Slag rate

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12.Different charging Practices.

13.Use of Auxiliary fuel

14.Decrease in breakdown, repair and down time.

2.1 Preparation and concentration of iron ore:-

A Blast furnace operator would now rarely orgue with the statement that, all other things being equal. The most important element in blast furnace production & performance is the condition of the burden

In Bhilai steel plant the development in the field of iron making (Blast furnaces) have always been directed to increasing the productivity of blast furnaces at minimum of fuel consumption (ie coke rate). This can be achieved if better quality change materials. With respect to their uniform size adequate strength and good reducibility, are consistently med to run the furnaces

Iron ore charged in the furnace should ideally pores the following properties

Physical :

Close size range

Low swelling tendency during reduction

A high softening temperature with a narrow temp range of fusion

Chemical:-

A high percentage of iron & low gragve contents.

A low percentage of silica, alumina etc. and a low alumina / silica ratio.

The total iron are requirement of BSP in met from a group of mines at Dalli Rajhara

There are five working mines these names along with quality of iron ore are as: blending. The ore feed in crushed in three stages and screened to produce (i) B.F lumps I e 10-40 mm. and

Sinter fines (-10 mm) grade ore at dalhi has lower Fe & high alumina, and thus requires beneficiation by wet processing by two stage crushing, wet screening, scrubbing and classification to produce lump (10 to 40 mm. ) and fines (-10 m.m.).

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finally iron ore used at Blast furnace Bhilai in of following specification.

Chemical analysis :- Fe = 64.0% (Minimum)

Sio2 = 2.5 0.5%

P = 0.10% maximum.

= 0.88% Maximum

Size range :- 10 - 40 m.m

Softening melting range :- 1175 – 1540 0 C

Good quality iron ore have alumina content less than 1% in contrast to rom ore which has approximately 2%. This high alumina percentage makes blast furnace slag highly viscous, which is normally tackled by resorting to relatively high slag volume operation (350–500 kg / thm) This decreases the productivity of Bhilai blast furnaces and also results in increased fuel rates.

Name of mine Fe% Si o2 % Al2o3 %

1. Rajhara Mechanized 67.33 % 1.76% 0.84%

2. Dalli Mechanized 63.80 % 4.52% 2.22%

3. Jharan Dalli 63.31 % 4.21% 1.90%

4. Dalli Manual 62.10 % 4.81% 2.61%

5. Mahamaya 62.00 % 5.00% 2.90%

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The iron ore occurring in the above deposits in mainly Hematite (Fe2 o3). Principal ore types include Massive ore, laminated ore, and high grade powdery ore also known as Blue dust or HGF. Wastes occurring in these deposits include laterite, shake & Phyllites. The horst rock for the iron ore hematite in known as Banded Hematite Quartzite (BHQ).

All the mines are worked by open cast methods with a combination of fully mechanized, or partly mechanized and partly manual means. Crawler mounted drilling rings are used to drill sown of holes of 6/12 meters deep for manual / mechanized mine. This blasted material is known as ROM is transported to processing plant. (Run of mine)

Two processing plants have been set up for processing of iron ore, the first being dry circuit plant installed at Rajhara, because iron ore from Rajhara mechanised mine is rich in Fe content.

Iron ore from Dalli having lower Fe % & higher percentage of alumina, has a wet circuit plant

High grade ore from Rajhara is used to improve quality of ore from Jharandalli and Mahamaya mines, by

Other than Alumina, Silica%, fluctuation in Fe%, Higher% of undersize in iron ore lump, moisture% (wet ore) all affects the productivity & coke rate & finally the cost of hot metal.

Increase in Fe in iron ore burden by 1 % will increase productivity of hot metal by 1.5% -2% & decrease coke rate by 0.8 to 1.2 %.

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2.2 * Coke quality:-

As we have already discussed the role of coke in B.F. Process.

The carbon content of coke should be maximum for it to be a good fuel. In other words it should contain minimum of ash and other deleterious impieties.

As a regenerator of reducing gases and as a heat produces it should have a high reactivity with O2 Co2 and water vapour.

Permeability of the charge, Particularly in the born region. Where every thing else except coke in either plastic or molten in maintain by the coke only. The coke should therefore be of a narrow size ranges and suffer minimal breakdown in its passage to and through the furnace until it burnis at tuyer level

The role of coke as a fuel and as a generator of reducing gases considerably reduced by the use of higher temp. blast and injection of auxiliary fuels in the furnace. Thin has been developed to the extent of achieving coke rate as low as nearly 275 – 300 kg / thm in some of the most modern furnaces below this value seriously decreasing the permeability of the charge. (this function of coke is of relatively greater importance than its heat generation and ore reducing functions.)

IN OTHER WORD’S

“ A MODERN BLAST FURNACE CAN NOT BE RUN WITHOUT A CERTAIN AMOUNT OF COKE AS A CHARGE MATERIAL”

* Factors affecting coke quality

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* Coal quality – (i) Chemistry (ii) Rank (iii) Coking Properties

*Coal preparation * carbonizing & handling

The quality of coke in related to the quality of coal its processing and subsequent carbonization process. There variables therefore needed to adjust to whatever extent feasible, to obtain the required quality of coke.

Quality requirement of coke:-

Quality of coke should be such that it gives minimum of operational difficulties and maximum of production rates at minimum of coke consumption.

1) Chemical composition as determined in tennis of the content of fixed carbon, ash , Sulpher, phosphorus and other deleterious impurities. (Moisture. Voltie matter etc.)

2) Reactivity as determined by its physical structure ie. Cellular structure and porosity. (CRI)

3) Thermal stability at high temp. (CSR)

4) Strength & agrarian resistance (M40 & M10)

5) Size range.

For efficient B.F. Coke rate & Productivity the desired value of above parameter are as.

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Characteristics Coke Desired Value

Size, m.m 25-80 > 80%

Physical Moisture < 4%

Porosity 40 -45 %

Strength M40 > 75%

M10 < 6%

CSR > 62%

Reactivity CRI 22 - 26%

Ash < 15%

V.M < 0.8 %

Chemical Sulpher < 0.8 %

Phosphorous < 0.1 %

Alkali < 2 %

Analysis of Bhilai B.F. Coke (On dry basis) obtained from coal blend charge in given below.

1) Moisture - 4.5 to 6.5 %

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2) Ash - 15.5 to 17 %

3) Volatile matter – 0.8 to 1 %

4) Sulpher – 0.65 % max

5) Fixed carbon – 79 to 81 %

6) M40 > 80%

7) M10 7.5 to 8.5 %

Note :- Comparing with good quality coke it is seen Moisture, Ash, V.M & M10 values of Bhilai B.F Coke is in inferior side & it affect the coke rate & Productivity as below.

Effect of coke quality on B.F performance.

Effect on

Factors Change Coke rate B.F Productivity

Coke Ash -1% -2% +2%

Fixed Carbon +1% -1% -

Sulpher -0.01 % -1% +0.8%

M10 -1 point - 2% + 2.5 %

M40 +1 Point -1.5% +1.3%

CSR +1 Point -0.2% +1.4 %

2.3) Use of sinter:-

Sintering in essentially a process of heating of mass of fine particles to the stage of incipient fusion (temperature little below the melting or softening point) for the

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purpose of agglomerating them into lumps.

In iron ore sintering the aim is to produce a strong but porous agglomerate from an uncompacted mass.

The process of sintering was originally developed merely to agglomerate the ore fines generated in mines (as in Blast furnace lump ore is a need of process). Once the beneficial aspects of sinter as part of blast furnace burden were realised, the physical properties and chemical constitution of sinter came to be examined more closely.

The understanding of the ideal properties of burden and the possibilities of achieving them in the sinter developed hand – in – hand. The object of sintering therefore enlarged and they are:

i) To increase the size of ore fines to a level acceptable to the blast furnace.

ii) To form a strong agglomerate with high bulk reducibility.

iii) To remove volatiles like CO2, H2O, Sulphur etc. (depends upon type of ore fines used)

iv) To incorporate flux in the burden.

In Bhilai Steel Plant 3 sinter plants are in operation

1) Sinter plant – 1, having 4 sinter m/c of area 50 m2 each. It has the capacity of 2.04 MT/Year sinter production.

2) Sinter plant -2:- It also have 4 machines with three have area 75 m2 and 4th one with 80 m2 area, with total capacity 3.137 MT /year.

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3) Sinter plant -3:- At present having one sinter m/c of area 320 m2 with a capacity of 3.2 MT/year. (Provision for one more m/c of same capacity is provided for incorporation in future.)

All these machines works on the principle of Dwight – Lloyd process – down draft system.

Initially the acceptability of sinter was very poor at blast furnace, and the sinter process was for utilization of metallurgical waste of mines and plant viz iron ore fines, limestone chips, flue dust ,mill scale etc.

Later on the importance of sinter gained momentum and it was accepted as a major raw material in B.F burden due to its good metallurgical properties. Thus the requirement of sinter went up necessitating the setting up of further sinter plants.

SP – 3 facilitates production of super flux sinter (baricity 1.6 to 2.2) consisting of approx. 70% iron bearing input in Blast furnace charge burden. (BF7)

Presently in Bhilai Steel Plant 65% average sinter burden in being used in Blast furnace.

The major advantage of increasing sinter % in burden in Bhilai blast furnace are as:-

1) Utilization of metallurgical waste of plant & mines (Viz iron ore fires, coke breeze, lime, dolomite etc. )

2) Better reducibility & other high temp. properties of mixed burden

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3) In creased B.F Productivity.

4) Improved quality of hot metal.

5) Use of super fluxed sinter eliminates top charging of raw flux in BF

Which results in Reduction in coke rate in Blast furnace?

Softening – melting characteristics of Iron bearing materials

S.No Material with Basicity

Softening Temp,0C (T1)

Melting temp, 0C (T2)

Softening– melting range

(T2-T1) 0C

1) Lump Ore 1175 1540 365

2) Sinter (Basicity 2.53)

1332 1600 268

3) Sinter (Basicity 2.08)

1340 1580 240

4) Sinter (Basicity 1.8)

1345 1570 225

5) Sinter 70% + I/Ore 30% (Basicity 2.08)

1265 1485 220

So it is clear from above table that 70% sinter + 30% iron ore burden gives lower softening & melting temp. and simultaneously lower range of softening & melting which is very good for blast furnace working.

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Other then this sinter gives advantage in the furnace operation in following ways:

1) Gas Distribution:-

* Narrow Cohesive Zone.

* Cohesive zone is lower down in the furnace

* Uniform gas distribution.

* Better aerodynamics

* More wind can be blown (Better acceptance.)

2) RAFT :- Can be increased, resulting coke saving.

3) Quality of hot metal:-

* Low volume of dripping zone

* Lower silicon

* (But) Physically hot metal.

* Smoother cast house operation

An extensive study regarding the use of sinter in B.F shows that:-

1) Trends in the production figures show that an increase in the sinter content of burden from small values to 40 to 60% has a greater influence on furnace performance as compared to increase from 60 to 100%.

In lower ranges every 1% increase in sinter % increases the output by about 0.35% and reduces the coke rate by about 0.3%.

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While changing from 50 – 60% to further more the respective values are 0.14% and 0.15 %.

2) Calcinations of limestone inside the blast furnace is very expensive of carbon.

Approximately 60 -70 kg C / 100 kg of CO2 (230 kg. CaCO3) are saved by transferring the calcinations work to the sinter strand.

3) Typical analysis of Bhilai Steel plant B.F skip sinter is

Fe = 54 to 55 %

FeO = 8 to 10 % * Size = 5 to 40 mm

SiO2 = 6% * R D I = 23.25

Al2O3 = 3%

CaO = 11 to 12% * Softening melting range

MgO = 2.5 to 3% 1330 – 15500 C

4) Each 1% increase in sinter Fe decrease coke rate and productivity increases.

While % SiO2 & Al2O3 when rises in sinter result in rise in slag volume.

While a compromise on FeO need to be made due to opposing requirement ie for higher cold strength, lower R D I and higher softening temp. High FeO is needed. Simultaneously it adversely affects the reducibility of sinter, hence FeO should be optimum for balancing both strength & reducibility characteristics of sinter.

Lime (CaO) in sinter stabilizes the liquids temp. of primary FeO – Al2O3 – SiO2

slag. The melting point of which would otherwise rise steeply as FeO is reduced in bosh.

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Lime rich bosh slag hinders reduction of silica, absorbs vaporized silicon and sulpher to produce low Si - low S iron.

The slag characteristics are partly attained in the sinter itself so that the transformation to the final slag is rapid but gradual and occurs at a relatively lower & narrower temp. range.

Hence super fluxing and higher % of sinter in burden saves much more coke in the furnace resulting better (improved) Productivity.

2.04

Hot blast temp:-

An enormous amount of air (about 5 kg) in used for combustion of 1kg coke at the tuyere. For efficient carbon utilization the air is preheated which increases the heat input as well as the tuyere gas temperature, ie. flame temperature,

The total available heat per kg C becomes larger with increasing blast temperature.

It is well known that the use of higher blast temperature results in a saving of coke and in an increase in productivity. The saving in mainly due to an increased supply of variable heat through the blast in order to reduce the tuyere coke consumption.

Following the principle of coke rate calculation it is calculated that about 4 kg C can be saved for every 100 kg of tuyere carbon per 1000 C rise in blast temperature.

Due to higher hot blast temperature operation following changes occur in the furnace:

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1) decrease in the amount of tuyere gas CO per THM

2) increase in direct reduction

3) decrease in the tuyere gas and hence top gas volume.

4) increase in (CO+CO2) and hence a decrease of nitrogen in the furnace gas caused by increased direct reduction

5) increase in the ηco

6) An increase in the top gas calorific value because of lowered nitrogen content

although the ηco increases.

7) A decrease in the top gas temperature because of a smaller volume of gas reaching the 9000c level in the stack.

All these are clear from fig. no. Pg 389, 390 AKB The decrease in indirect reduction with increasing blast temperature in apparent.

However the blast temperature and, therefore the flame temperature cannot be increased arbitrarily. If the flame temperature is increased over a certain optimum, the furnace starts to show erratic movement or result in hanging Even an increase in the coke rate is possible. Stock descent becomes irregular, thin hanging is due to fallowing possibilities:

a) descent of slog fusion zone to bosh incline,

b) increased formation of garcons’ silicon monoxide at high flame temperature and its subsequent reoxidation and condensation at higher levels, blockage of void age hindering gas flow;

c) Increased volatilization of alkali metals, Na and K at high flame temperature formation of their cyanides, Condensation of cyanides ,to viscous liquids which give the burden material together, choke the voids, and hence retard gas flow

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d) Flooding of slog in the coke grid due to increased tuyere gas velocity.

In any case, experience shown that the optimum flame temperature is limited by the quality of the burden, furnace profile and method of operation, A decrease in the blast temperature or injection of coolants like steam invariably removes the hot hanging.

Prepared burden (fluxed Sinter) accept the higher blast temperature compare to raw ore, This is because in the case of fluxed burden the gas solid temperature difference in much smatter which together with the fact that the slog in preformed, permits the use of higher blast temp.

There are different opinions as to the amount of coke saved in practice by increasing the blast temperature; It is generally believed that the savings are more at lower blast temperature. Than at the higher ones about 4% / 1000c at 9000C, 3% / 1000C at 10000 C and 2% / 1000C at 11000C.

At a coke rate of 635 kg / THM, the total savings amounted to 12% on raising the blast temperature from 8500C to 12500C with a simultaneous increase in iron output by about 27%. This results in remarkable cost savings.

2.05 Blast volume:-

An increased blast volume rate means increased oxygen input in unit time which results in an increased coke burning rate. the coke burning rate is approximately proportional to oxygen input

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A large blast volume will be accept by the furnace if the permeability of the stock column in increased simultaneously so that the material descent and gas distribution are uniform throughout the vertical and horizontal cross-sections. This is ensured by the use of mechanically strong, abrasive resistant, graded and sized ore, sinter and coke and their proper distribution at the top

The resistance to gas flow due to smaller particle increases the blast pressure hence a considerably high blast pressure is needed for overcoming the resistance causing high flue dust emission , channeling , hanging , slipping etc and resulting in increased coke rate and decreased production

The acceptance of Blast volume is not only depend upon the size range of raw materials but also on their strength ,flame temperature, softening melting temperature, quality of slag, high top pressure etc .

2.06 Quality of hot metal :-

Quality of hot metal delivered to steel making in evaluated based on hot metal chemistry mainly silicon, sulfer and hot metal temperature .

Steel making process needs a consistent feed product. Ifhot metal chemistry in variated the same must be adjusted for every heat.

In general, hot metal silicon sulfur temperature is the principal parameter that the day to day operators make adjustments to control.

a) SILICON CONTROL:-

Optimum hot metal silicon level is plant dependent. In most of steel plants, hot metal with lower silicon content was found to reduce raw steel cost, Same in the case with Bhilai steel plant also. One of the most common tasks for day to day operation of Blast furnace in lower hot meral silicon, Hot metal silicon unfortunately, thin may not be desirable, It is best to lower silicon without affecting hot metal temperature I.e. To change the silicon temperature relationship.

Three means of lowering hot metal silicon may be deducted from the mechanism by which silicon enters the hot metal

a) Suppress SiO Gas generationb)

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Lower flame temperatures.

Lower SiO2 input: reduce total SiO2 input from coke and other burdening materials.

Increase total furnace pressure: Increase top pressure, use higher wind rates.

(b) Reduce contact time

Reduce contact time between hot metal and slag: dry hearth practice, regular casting and flushing, clean hearth practice.

© Reduce silica activity

Increase in basicity

Adjust slag chemistry: CaO and SiO2 have more impact on silica activity than MgO and Al2O3.

b) SULFUR CONTROL:-

Hot metal sulfur is mainly controlled by the slag basicity and sulfur input. Sulfur control can be either done internally of externally. The choice is based on economics. If the decision is to use the furnace as desulfurizer, hot metal sulfur can be reduced by the following means:

(a)  Control sulfur input

Key parameters:Reduce sulfur load in burden and cokeReduce sulfur in the injectants.

(b)  Relation kineticsKey parameters:Hearth temperature: A higher temperature increases the rate of reaction.Pressure : Higher pressure, Higher sulfur to the metal

© SlagKey parameters:Slag basicity : Higher Basicity = higher sulfur removal

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Slag composition: CaO is better desulfurizer than MgO, Al2O3 is less acid than SiO2.

Increase slag volume.Optimize slag viscosity.By this we understand how we have to control silicon and sulfur its very clean that both this element have very high impact on quality of hot metal, variation in both not only affects steel making process but also the performance of Blast furnace its coke rate & productivity.

As The control parameter for same in helped in that direction.High silicon results in less acceptance of blast. Wide range of softening melting zone, increased pressure of blast, While lower silicon results in low temperature of slag. Poor fluidity & less drainage of slag from furnace all these leads to affect productivity & hence coke rate.

Same in the case with sulpher also.

2.07 SLAG RATE:-

Hot metal is extracted from ores which are always associated with impurities, mainly oxides,called gangue . During the extraction of the metal the gangue is removed, by the addition of flux, in the form of slag which is insoluble in the metal. In the iron ores and coke ash the impurities are mainly acidic silica and alumina. The fluxes are basic lime and magnesia, The other components in the Blast furnace slag which together may not amount to more than 5 percent are FeO, MnO,TiO2 , s and others.

The nature, composition and amount of slag (slag rate) ultimately control the composition of the Pig iron and the productivity of blast furnace. It should be noted that the most important purpose of slag control is the control of sulpher, since sulpher is the key to iron quality. It is un economical to produce a low – P, low-Si and High –S iron . There is a wide range of slag composition in terms of Cao, SiO2 ,Al2O3

and MgO, Where the slag is a homogeneous liquid of low viscosity at the hearth slag temperature (1400-1450 0C ) But the difficulty arises when the slag has to have certain minimum basicity and bulk for the control of sulpher.

The use of optimum slag composition would give minimum sulpher in

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iron and minimum slag volume, resulting in maximum production (high productivity) and minimum Fuel (lower coke rate) hence minimum fuel cost.

2.08 Different charging Practices:- (Burden distribution)

Burden distribution is one major factor which can contribute to a reduction in coke rate by improving the gas utilization.

-In high Productivity furnace especially, burden distribution control becomes critical.

A strong central gas flow with controlled flow along the walls (to prevent wall) is torrential for smooth operation of the furnace. Moderate temp. extending over a greater part of radius.

In Bhilai Blast furnaces burden material reaches to the top of the furnace by skip can & then it in distributed into the furnace.

For this in B.F 1 & 2 double bell charging system is there (see fig.) In B.F-3 along with bells Rotating changing unit (R C U) in provided (fig.) B.F. 4,5,6,7 are equipped with Paul – with Bell less top (B I T) changing system, which replaces bells with changing beam, upper material gate, upper sealing valve, lower material gate and lower sealing valve (Sec fig.) This system also has a gearbox to operate a rotating chute. The chute distributes the material inside the furnace peripherally in different rings. This facilitates better burden distribution inside the furnace.

To facilitate smooth working of furnace, the coke & son coke material is to be distributed in a particular fashion in the whole circumference of the blast furnace. For those different charging sequence in fallowed. A typical charging sequence in given below.

Sequence 1 : c o c / c o o c c / c c o o c cSequence 2 : c c o o

Each charging cycle consist of 5 sequences of either 1 or 2 exclusively or in combination depending on the periphery conditions, Generally in Bell – less top furnaces the 2nd sequence in fallowed ie. c c o o .

C = Coke; O = Non coke ie ore, sinter, Mn ore, Limestone etc.

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The material is distributed in the B.F in different sectors (see. fig.)

The production rate of blast furnace is directly determined by two important factor viz

i) The rate of reduction of iron oxide. And

ii) The rate of heating of burden. There two factors are related with quantity of blast that goes through the finance ie. its “driving rate”.

The efficiency with which both of the above functions are met in the finance stack Predominantly determines the furnace productivity.

The uniformity of distribution of reducing gases through out the horizontal and the vertical cross section of the furnace is an essential fitness for efficient reduction and heating of the burden.

The initial distribution of charge in the throat usually persists throughout the furnace shaft.

The gas utilization, in other words the coke rate, in a function of burden distribution.

It has been found that additional each percent of co utilized for reduction means a saving of almost 7 kg of coke per ton of iron produced.

Hence the question of distribution of change materials in the throat of the furnace, under given conditions plays a very dominant role in deciding the performance of furnace.

With conventional belt top changing system the flexibility of burden distribution is much limited. While Bell less charging leads to much more size segregation across the radius due to slower discharge rate of raw materials.

2.09 Cast house practice:-

An excellent cast house operation is an important factor in a low cost high productivity blast furnace operation.

The cast house functional design, operational practices, refractory technology, automation & environmental requirements are key to meet

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today’s demand for greater reliability hence high productivity which resulting lower coke rate.

The cast house is the most labour intensive area in the entire blast furnace operation. Its design must be fully integrated with the expected hot metal production, health volume, and tapping practice with minimum use of labour, maintenance, material and improving working environment.

In cast house practice the prime objective is to remove liquid iron from the blast furnace at a casting rate and through a number of casts per day that is determined by the smelting rate, effective hearth volume and the desire of maintain the hearth in a “dry” condition.

The key to cost reduction in refractory consumption is to optimize the length, and extend the campaign life, of the iron through and not metal runner system.

* following are the factors which affects greatly for improving productivity & cost effectiveness through cast house practice:-

1) Symmetrical arrangement.

2) Relatively short iron runners.

3) Relatively short slog runner.

4) Development and use of cast house refractory’s which are more, resistant to erosion and corrosion by iron & slog.

5) Less time employed by cast house crews in between – cast maintenance, and through and runner repair.

6) Multiple tap holes.

All this helps in faster drainage of hot metal & slag, No not dry cast, hence better quality, good productivity resulting less fuel consumption.

In Bhilai B.F. – 1 & 2 & 3 have single cast house with single tap hole simultaneously slog is collected in slog ladles.

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B.F – 4,5,6 have single cast house but twin tap hole, 400 apart, equipped with slag granulation plant (B.F. 4&5 – INBA. while BF-6 cost house slog granulation plant)

B.F.7 have twin cost house each have one tap hole & both side C.H.S.G.P. two unit each side. (Best design)

2.10 Not dry cast:-

The aim of B.F operator is to run the furnace always in stable condition

Casting procedure has been based on “dry hearth practice” or “casting the furnace empty” and as the term implies, operates on the principle of keeping the liquid contents of the hearth operating below a safe maximum level and draining the hearth as completely as possible at each cast.

Apart from promoting process stability, this mode of operation permits the furnace to be taken off blast at any time, without having to worry about the level of liquid in the furnace.

Whenever due to any reason when any cast in closed “NOT DRY” charges in all aspects of blast furnace operation occur such as

-              Difficulty in maintaining wind volume-              increasing blast pressure.-              slowing in irregular burden des cont-              distortion of reducing gas flow exiting the receway towards the f/c walls.

and a general “tightening” of furnace conditions.

All of these undesirable symptoms affect slip rate hence production / Productivity. After Not dry cast, next cast to be open as soon as possible If monkey (slog notch) in operation, open slog notch to decrease the level of fluids in the hearth.

2.11 Tap hole clay:-

No part of the furnace requires more case and attention than the tap hole. The physical location of the tap hole in the lower hearth mean that it is subjected to the highest pressures prevailing in the furnace, ie. blast pressure plus Ferro static pressure of the accumulated iron

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and slag.

An furnaces have become layer, with corresponding increases of pressure and productivity, tap hole clay have had to be developed to meet the resulting more stringent demand made upon them.

As we all know life of Blast furnace depends largely on erosion of refractory lining of the hearth wall. Erosion of hearth takes place because of metal flow in the hearth specially the extent of circumferential flow near the hearth wall region.

A longer tap hole reduces the intensity of metal flow in the circumferential region, and reduces the wall lining erosion. A shorter tap hole enhances the circumferential flow and increases the wall living erosion. The control of the tap hole length is regarded as one of the indispensable measures to achieve a longer life of blast furnace.

Due to bad quality of clay so many tapping related Problem occur such as

1) Hard tap hole2) Fast flow3) Short tap hole4) False flow5) Spitting behavior6) Not dry craft

All these results in poor drainage of metal & blog from furnace, resulting change in quality of hot metal poor acceptance of blast, rise in hot blast pressure and finally Productivity suffers resulting rise in coke rate too.

Good quality of clay in prime importance for higher production.

2.12 High Top Pressure :-

Use of High top pressure influence the coke ate (and hence the productivity) mainly because

i) an increased gas pressure in the furnace increases the rate of reduction of iron oxides, decreases direct reduction and hence reduces the coke rate.

ii) a decrease in linear gas velocity because of high top pressure increases the gas solid contact time, decreases direct reduction and

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hence reduces the coke rate;

HTP improves gas permeability in the furnace and promoter a more uniform gas distribution which in turn further decreases direct reduction.

iii) More uniform operation with lower and more consistent hot metal silicon content have been claimed to be the benefit of high to pressure.

The Bhilai blast furnace with high top pressures have shown a huge decreases in Si – content of the hot metal because of application of high top pr.

iv) High top pressure markedly decreases channeling and hence low dust losses in outgoing gases and hence load on gas cleaning system is there by reduced.

v) The solution low reaction (CO2 + C 2 CO) in suppressed because of rise in pressure. In other words the Bourdon equilibrium

[CO2 + C 2 co] moves to left because of HTP and may consequently have beneficial effect on coke consumption.

fig. (pg. 426 Akb) shows the decrease in direct reduction carbon with increasing top pressure for constant productivity and increase in direct reduction carbon with increasing productivity at constant top pressure. Since productivity increases with increasing top pressure because of increased gas man increasing top pressure because of increased gas man flow rate, the extend of coke saved will depend upon the linear gas velocity.

In totality HTP promotes stable furnace operation for long periods in both large and medium capacity furnaces hence beneficial effects on furnace campaign.

2.13 Use of Blast additives:-

The primary purpose of using inject ants with the blast in profitability which depends upon the relative price of coke and inject ants and the amount of coke that can be saved per unit of the latter ie upon the replacement ratio:

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Replacement ratio =

In addition such injections generally causes a smoother furnace movement and give rise to a higher productivity specially with oxygen containing additives, e.g humidified or oxygenated air or oxygen plus fuel additives.

The additives used as part replacement of Coke are those which can not be changed from the top. They may be:

i) Gascom, such as oxygen, steam, natural gas, coke oven gas, reformed gas; (in B.S. P it in O2 & steam) All B.F

ii) Liquids, much as fuel oil, tan, oil – cont slurry, naphtha (In B.S.P tax, in B.F-2, 3 & 4)

iii) Solids, such as, Pulverised coal anthracite etc.

(in B.S.P pulverized coal in B.F. 1,5,6,7)

These additives obviously cannot play the role of coke for providing bed permeability in the dry zone or mechanical support to the charge column in the wet bosh zone but otherwise they perform the same chemical & thermal function the latter however at a much reduced scale. These is because except oxygen all the above additives lower the flame temperature.

The Blast furnace works through a balance between the thermal & Chemical (reductant) energy requirement since for production of 1 THM. The amount of a removed from iron oxide (Washita oxygen) in more or less a fixed quantity & hence minimum amount of reluctant

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necessary for its elimination is also fixed.

The optimum fuel rate is obtained only when the heat requirement is satisfied along with the minimum reduction requirement. (In B.F fuel applies both while sensible heat of blast supplying part of the thermal energy).

The replacement ratio depends upon the sum of the tuyere & direct reduction carbon saved.

The me of blast additives affects the fuel rate of a burden in several ways, they being mainly due to changes in:

i) flame temperature

ii) bosh gas composition and volume.

iii) Thermal efficiency ie. the CO/CO2 ratio and temp. of the top gas;

iv) Operational efficiency, ie. Proportion of direct / indirect reduction.

v) Slag volume & basicity.

vi) Iron quality.

vii) Production efficiency.

Humidification of Blast:-

Moisture presence in the hot blast results in water gas reaction when it comes in contact with hot coke in front of the tuyere as :

H2O + C = CO + H2

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Although it’s a endothermic reaction but with combined use of oxygen enrichment & high not blast temp. its beneficial.

Moist blast generates more reducing gas per unit volume than that of dry blast. The hydrogen generated acts as a reducing gas in addition to carbon monoxide, and hence coke rate would be correspondingly reduced. Some of endothermic heat is compensated by the exothermic reduction (reduction reaction).

For humidification steam in introduced in the cold blast before it in preheated in the stoves, (If it in introduced in the hot blast since the steam temperature will not be as close to that of the hot blast, it will have cooling effect which in not desirable).

Compensating Rmp. Increase being about 8 – 100 C / 1 gm H2O / NM3 of blast.

A study shown:-

A 9000 C hot blast without addition of steam (moisture), when added with 20 gm H2O / Nm3 and blast temperature rises up to 11000c, an increase of 5-6% in production is marked.

* Steam increases the production rate for the following reasons:

i) higher gasifying power which intensities coke consumption in the raceway.

ii) smoothens the temperature gradient and facilitates block descent.

iii) enlarges the combustion zone and accelerates burden descent, heats up the axial zone and maintain thermal state of the hearth.

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iv) even with in complete temperature compensation, the coke rate may not rise because of higher reducing power and higher heat transfer coefficient of hydrogen.

v) decreases pressure loss due to lower density & viscosity of hydrogen. The blast pressure many drop even by 0.1 – 0.2 atm. Which means the furnace can be blown at higher rate.

OXYGEN ENTICHMENT OFBLAST :-

For every unit weight of coke burnt at the tuyere by the air blast, nearly 4-5 unit weight of nitrogen of the blast are also heated to nearly 20000 c. Although large amount of furnace gases are beneficial for heat transfer in the stack, Oxygen enrichment lowers the nitrogen content of the blast and decreases the blast volume per unit of carbon burned as well as the bosh gas volume per THM.

for the same blast volume or the volume of bosh gas generated per unit time, oxygenation would give increased coke driving rate / (coke burning rate). As oxygen help in heat transfer. An enrichment of only 2% (by weight) oxygen reduces the nitrogen burden by about 4 units. Per unit weight of coke and hence a higher temp. in possible.

Therein however a limit to which higher temperature in front of tuyeres is desirable since any excess over that causes bridging and sticking of the stock and higher silicon content in pig. Iron.

It varies (O2 enrichment) 21 -30 % depending upon the burden and its acceptance of high flame temp. In iron making coke burning rate increases in proportion to the increase in oxygen, An increase from 21 to 26 percentage would increases the burning rate by

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(26-21) x = 24 percentage

The productivity would increase by approximately the same amount. A study shown with 27% oxygen in the blast results in the average production increased by 29%. The coke rate decreased simultaneously by 9% and the dust emissions by 8%. (for every percentage increase in O2

(content) (Increase in production rate of 3 to 4% in obtained)

Note:-

Combined use of O2 enrichment and humidification of blast furnace is a unique method of blast furnace process control.

Control of blast furnace by coke rate in not effective before few hours after the changes whereas variation in O2 enrichment and humidification can control the temperature almost immediately, it can also be monitored continuously.

* Fuel Injection:-

The necessity of adopt fuel injection in a blast furnaces arises from the fact that coke is not only costly but it is becoming more and more sconce and hence it should be replaced by other cheaper and readily available fuels, as far as in feasible, to run blast furnaces without imposing their efficiency.

The heat producing function of coke in partially replaced by injecting auxiliary fuels in the tuyeres either solid, liquid gaseous fuels can be injected in the tuyeres.

In Bhilai steel plant auxilliary fuel injection is connected with All 7 blast

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furnace in

B.F 1,5,6, & 7 – solid fuel – pulverised coal

& in B.F 2,3,&4 – liquid fuel – coal tar is injected (which is by product of ore coke oven by product plant)

The choice of the type of fuel for injection almost entirely depends on its availability, economy and feasibility of injection.

The replacement ratio of coke by injected fuel depends an the practice & quality of the fuels, as practice the same in :-

1) Coal = 1.0 kg coke /kg coal.

2) Tar = 1.3 kg coke / kg Tar.

3) Tuyere gas formed on gasification of hydrocarbons are richer in reducer gases.

4) Hydrocarbons caners smoother furnace movement

5) Oving to the in her sent need for oxygen enrichment, hydrocarbons help in improving B.F productivity.

6) It is important to under stant:

Heat generated on gratification of auxiliary fuels is lower than the same on burning of coke due to

- lower carbon content of auxiliary fuels

- heat required for breaking of C – H bonds.

- Auxilliary fuels are injected at lower temp (30 – 900c). While coke reaches tuyeres in a preheated state.

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7) Auxiliary fuel need higher blast temp. and extra oxygen levels in blast for their complete burning.

8) The effectiveness of an auxiliary fuel in replacing coke is lagely determined by

- the extent to which the thermal deficit ariving out of its enhanced mage in composted. - the rate at which oxygen in made available for its complete combustion in the raceway.

9) Thermal compensation in given by

- Increasing hot blast temp.

- Enriching blast with oxygen.

- Reducing blast humidity.

All inject ants are coolants and need a compensating increase in the blast temp for obtaining high replacement ratio. The total amount of gas produced depends upon the relative amounts of tuyere carbon and inject ants. In the case of fuel injection. The bosh gas becomes enriched in the reductant gases Co & H2 and they increase the rate of iron oxide reduction.

It in true, because of much lower viscosity & density of H2 a H2 rich bosh gas will encounter smaller resistance to gas flow (lower Pressure drop & smoother furnace operation) and therefore, a high production rate can be expected, simultaneously decrease in coke rate resulting higher Non coke / coke ratio which affects the Permeability and other greater resistance to gas flow. (The cumulative effect of these opposing influence is extremely important to evaluate)

Hence Coke replacement by Auxiliary fuel injection because :-

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1) Auxiliary fuels contains hydrocarbons with varying C/H ratio.

2) Hydrogen is generated on burning of hydrocarbons

- It in more powerful reducing agent than co

- It help in in better heat transfer

- It has a faster rate of reaction

Comparative assessment of different fuels:-

Carbon Coal

(15% ash)

Coal tar

Natural gas

1) Caloritic value 8000 6300 8560

K Cal / kg

Or Kcal / Nm3

2) C/H ratio - 1.43 0.25

3) Heat generated

(Kcal /kg) or

(Kcal / N m 3 )

2200 1731 381

4) Blast required

to transform in to Co & H2

(Nm 3 / kg ) or Nm 3 / Nm 3

4.44 3.53 2.38

5) Tuyere gas

Co (%)

34.7 32.7 20.5

H2 (%) 0 12.2 41.0

Reduce gas (%) 34.7 44.9 61.5

6) Replacement - 1.1 1.3 1.3

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ratio

7) O2 required for compensation

( %)

2 2 2

Replacement ratio depends upon a number of factors like:-

- Inherent characteristics of auxiliary fuel (C/h ratio, finances, flow ability, dispersion)

- Amount of thermal compensation provided.

Relative amount of “C” in coke & auxiliary fuel used

Extend to which difficulties faced in B.F. operation in tackled.

ASSESSMENT OF INJECTANTS :-

Coal despite having the least replacement ratio in techno-economically the most suitable fuel for injection due to its lowest price and the least amount of thermal compensation required per unit weight injected.

With high amount of O2 enrichment coal can be injected to very high levels (> 250 kg / thm) and will result in maximum quantity of coke saved.

Low return in cases of tan in on account of their price.

Tan is the most difficult to handle on shop floor as it requires heating of the pipe lines during its transportation, contains solid in troubles and leaves behind residues after combustion .

Tan needs good dispersion to be achieved in tuyeres for their complete burning “otherwise they will create problem by relearning soot and affect B.F operation adversely.

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Whichever injectant is used, its regular supply must be ensued for maintaining the stability of B.F operation.

2.14 Break down, repair and down time:-

A Blast furnace once started is expected to run for nearly five years before it is due for complete relining and major repairs.

Iron making by blast furnace is mainly depends upon the degree of heat utilization. The degree of heat utilization is to a remarkable extent of 85-90 % which has been made possible because the blast furnace is an extremely efficient counter current heat exchange apparatus.

Any type of breakdown, planned repair or down time causes reduction of blast partly or fully other breakdown (like water leakage) etc. also affects its heat utilization.

As we know in blast furnace process high temp. blast with high volume is supplied and this blast volume is responsible for high productivity because higher blast volume is resulting higher oxygen input greater burning of coke, generation of huge amount of heat which in time gives high production. Better this whole process is continuous, better the productivity & lower in the coke rate is.

As blast furnace is very complex appoint us, continuous running of blast furnace is associated with proper running of its different sections. So maintenance practices should be planned such that it will make unplanned delays as minimum possible resulting minimum loss w.r.t Productivity & coke rate.

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CHAPTER 3

BLAST FURNACES AT BHILAI STEEL PLANT

AND SELECTION OF BF#5 FOR STUDY

Overview of Bhilai Blast furnaces:-

The blast furnace department of Bhilai Steel Plant is equipped with 7 Blast furnaces. All these furnaces have been commissioned in various phases of modernization.

The table below gives in short the details of these 7 furnaces:

Commissioning date

useful volume

working volume

Useful volume =

Hearth to stock level

Working volume

= Tuyere to stock level

1) B. F. – 1 04/02/1959 1033 m3 886 m3

2) B. F. – 2 28/12/1959 1033 m3 886 m3

3) B. F. – 3 28/12/1960 1033 m3 886 m3

4) B. F. – 4 08/12/1964 1719 m3 1491 m3

5) B. F. – 5 27/11/1966 1719 m3 1491 m3

6) B. F. – 6 31/07/1971 1719 m3 1491 m3

7) B. F. – 7 30/08/1987 2355 m3 2105 m3

All these furnaces are commissioned in various phases of modernization.

In 1 M. T. stage B. F. 1, 2, & 3 were commissioned.

2.5 M.T. stage B. F. 4, 5 & 6 were commissioned

4 M. T. stage B. F. 7 were commissioned

Further capacity enhancement took place recently in Feb. 2007 by modernizing BF No. 7

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At present the annual rated capacity of hot metal is 4.7 M. T. / annum.

COKE RATE AND PRODUCTION DATA OF BHILAI BLAST FURNACES:-

Year F/c Commissioned dt. & respective production

Production (Shop)

Coke Rate (Kg/ THM)

Hot Blast Temp. (0c)

1) 1958-59

B.F-1 36930 Ton

(04 / feb. /1959)

36930 Tons N.A N.A

2) 59-60 B.F.1&2 B.F.2(28/12/59) 77,310 Tons

4,48169 Tons N.A N.A

3) 60-61 B.F.1,2,&3 B.F.3 (28/12/60) 74,437

7,35,624,Tons N.A N.A

4) 64-65 1,2,3,&4 B.F.4 (08/12/1964) 84,157 tons

1.256 M.T 1024 (B.F.4)

7420C (B.F-

4)

829 (Shop) N.A

5) 66-67 1,2,3,4&5 B.F.5(on 27/11/66) 1,99,979

2.05 M.T 814(B.F.-5) 792 (Shop)

8170C

6) 71-72 1 to 6 B.F.6(on 31/07/71) 4,25,442 tons

2.125 MT 778 (B.F 6) 810 (Shop)

8420C 7780C

7) 87-88 1 to 7 B.F.7 (30/08/87) 329981 tons

2.556 M.T. 660 (B.F.-7) 730 (Shop)

8860C 7850C

8) 88-89 All 7 - 3.30 M.T 685 8170C

9) 92-93 All 7 - 4.04 M.T 641 8920C

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10) 93-94 All 7 - 4.25 M.T 642 9100C

11) 97-98 All 7 - 4.51 M.T 572 9560C

12) 03-04 All 7 - 4.93 M.T 503 9590C

13) 05-06 All 7 - 5.17 M.T 497 9630C

14) 08-09 All 7 - 5.38 M.T 491 9500C

15) 09-10 All 7 - 5.37 M.T 499 9220C

16) 10-11 All 7 - 5.708 M.T 497 9550C

Reason for selection of BF-5

As we have already discussed different factors which affects the coke

rate & productivity of Blast furnaces at Bhilai Steel Plant.

Out of all these seven furnaces Blast furnace # 5 is chosen for study and

data analysis because of following reasons

1. It’s a medium size 1719 m3 volume (useful) furnace

2. Oxygen enrichment

3. purchased clay

4. Slag granulation facility

5. Advance PLC & Computerized monitoring system at COCR & FFCR.

6. Pulverized coal injection (DC Technology)

7. Pneumatic actuators and Rockwell control logic PLC along with critical

back up instruments.

8. Up gradation in stove operation. (Hydraulic gas valves in burners of

stoves )

9. Deducting units for stock house

56

10. Improved cast house design provision of rocking manners.

11.Own GCP

12.Raw materials (especially iron are screening facility) Which makes

supply less troublesome.

13.Stove operation in Auto mode.

14.4 stoves (Healthy condition)

15.Coal dust injection facility.

16.Paul wurth BLT charging system

17. Improve cast house design, Provision of second tap hole, Castable

runners

18.BF 5 is having all 2 wire 4 – 20 mA instrument s Pneumatic actuators,

Yokogawa make DCS (CS 3000)for furnace & control logic PLC for

stoves, along with critical back up

19.Stoves automation to optimize the heating and blast period of stoves.

20. Hydraulic mud gun and drill m/c replacing the electro – mechanical

counter parts.

21.For better cooling of hearth bricks, separate independent cooling

system.

22.Consistency in furnace operation, (Scope for productivity

improvement)

57

BF #5 profile and diagrams:-

MAIN DIMENSIONS OF BLAST FURNACE # 5

Useful volume ( top of the hearth to stock level) 1719 m3

Working volume ( tuyer to stock level ) 1491 m3

Full height 31250 mm

Useful height 28500 mm

Top height 1900 mm

Top diameter 6000mm

Stack height 17800mm

Stack angle 84 0,42’,18”

Bosh height 3000mm

Belly height 2000mm

Bosh dia 10200mm

Bosh angle 79 0 ,36’,48”

Hearth height 3200mm

Hearth dia 9100mm

Number of tuyers 18

Number of tap hole 2

Monkey 0

Equipment and other details of blast furnace #5

58

1. Open loop water cooling system

2. Stack zone is having plate coolers

3. For charging furnace have BLT with single bin

4. Skip car charging system

5. Top pressure =1.1(maximum)

6. Single cast house with twin tap hole with 400 apart

7. INBA slag granulation plant

8. Four Russian design, horizontal fired, internal combustion chamber

stoves.

9. Hydraulic mud gun and drill machine

10.Pulverized coal auxiliary fuel injection

Space for diagrams:-

1) Body

2) BLT

3) Cooling arrangement

4) Cast house

5) Total view of BF-5

59

60

61

62

63

64

CHAPTER 4

INTERNATIONAL STANDARDS

WORLD STANDARD REGARDING SAME:-

S.No.

COUNTRY PRODUCTIVITY BURDEN INJECTANT

1) JAPAN 2.7 SINTER COAL

2) KOREA 2.7 SINTER COAL

3) USA 2.5 SINTER COAL

3.1 PELLETS GAS

4.2 PELLETS, HBI GAS

* HBI = 200 KG/T

4) CANADA 2.9 PELLETS OIL

5) SWEDEN 3.5 PELLETS COAL

6) FINLAND 3.4 SINTER OIL

7) BELGIUM 2.8 SINTER COAL

8) NETHERLAND

2.9 SINTER AND PELLETS

COAL

9) ARGENTINA 2.6 SINTER, LUMPS AND PELLETS

GAS

10) BRAZIL 2.8 SINTER COAL

11) CHINA 2.5 SINTER COAL

65

A common features of all the operation shown above is excellent raw material quality, fluxed pellets are prominent in the operation of the smaller furnaces while sinter in the predominant burden material in larges furnaces high quality coke in common to all operation.

Thin specific productivity values are almost all in the ranges of 2.5 to 3.4 in the recent past specific productivity levels of 2.0 to 2.5 were considered to be quite good. Exceptional productivity 4.2 to USA (A K middle town BF 3) is added by changing metallies. Mainly

H B I ( High brid iron ore) at higher rates > 200 kg / T.

The increased productivity accomplishments outlined above have been primarily the result of the evolution of reduction of total fuel rate. The very large newer furnaces shown above were designed and built for low fuel rate operation but the designers of there furnaces had the benefits of technical development.

Recent achievements

* Coke rate = 250 kg / Ton of hot metal

* Injectant = 250 kg / Ton of hot metal

* Total reductant = 500 kg / Ton of hot metal (or less then that)

All this possible became of the development like

High hot blast temp

High top pressure

Oxygen enrichment

Burden distribution & Permeability control.

Increased coal, gas & oil injection (maximum injectant)

Lower Possible fuel rates with metallic’s

66

INTERNATIONAL BENCHMARK:-

S.NO PARAMETERS PLANTS VALUE

1) Productivity (t/m3 / day B F # 7 Hoogovan (Netherland)

3.37

2) Coke rate (Kg/thm) B F # 7 Hoogovan (Netherland)

268

3) CDI (Kg / thm) B F # 3 Fukuyama NKK (Japan)

266

4) Hot Blast temp, (0C) Kcihin, Japan 1350

5) Top Pressure (Kg/Cm2) B F # 6 Posco, Korea 2.5

6) Slag rate (kg /thm) B F # 7 Hoogovan (Netherland)

203

7) Oxygen enrichment (%) B F # 7 Hoogovan (Netherland)

13.2

8) Oil injection (kg/thm) B F # 1 Rautarrukki (Finland)

100

9) Natural gas injection (Nm3 / thm)

(USSR) 130

10) Lowest silicon in hot metal, (%) B F # 5 Fukuyama NKK (Japan

0.17

11) Proportion of prepared burden, (%)

N K K, (Japan) 100

12) Campaign life, (Million, ton) B F # 6 , Chiba, Kawasaki (Japan)

60

67

CHAPTER 5

THEORY OF REGRESSION ANALYSIS

A Brief survey has been made on the use of statistical analysis in operation of Blast Furnace.

Introduction:-

Blast furnace is one of the most complex industrial reactor and remain some unsolved puzzles, such as blast furnace automation, prediction of inner thermal state its productivity, calculation of coke rate etc

And as we know there are many factors which affect the Blast furnace productivity & hence coke rate. Therefore, statistical techniques are useful, and often even necessary, for determining the precision of the measurement and for drawing valid conclusion from the data.

For the economic operation of a Blast furnace, it is very important that furnace give maximum possible productivity with minimum of coke rate, hence furnace needs to be strictly monitored and controlled.

With the help of regression analysis technique when data is analyzed it is approximately possible to perform the predictive task.

All these results can acts as a guide to aid the Blast furnace operators for judging the possible productivity & coke rate in time and further provide an indication for them to determine the direction of controlling blast furnace in advance.

REGRESSION ANALYSIS:-

The term regression is used in statistics to refer to the determination of a functional relationship between one or more independent variables

Regression analysis is a statistical forecasting model, that is concerted with describing and evaluating the relationship between a given variable ( usually called the dependent variable) and one or more other variables ( usually called the independent variables).

Regression techniques are ordinarily used where it is assumed that a fixed but unknown relationship exists between the x & y populations but the random errors in the measurements prevents a reliable determination of the relationship by inspection. The term linear regression which is also called method of least

68

square because the line which results from the analysis has the property that the sum of the squares of vertical deviations of observations from this line is smaller than the corresponding sum of the squares of deviations from any other line. Multiple regressions, where there are two of more independent variables in the regression equation, is an extension of this analysis, and curvilinear regression where a cured line is fitted to the data, is a further refinement.

LINEAR REGRESSION:-

It frequently happens that the scatter diagram indicates an association between the variables, x and y, the distribution of dots being denser in the neighborhood of a certain line which may be called a line of regression. The equation of such a line indicates a functional relationship to which the association of the variables approximates more of less roughly.

Now attention is confined to the two straight lines one of which gives the closest estimate a straight line can give to the average values of Y for each specified valve of x while the other gives corresponding estimate of x for the given value of y. These are called the lines of regression of y on x and x on y respectively.

The equation of the line of regression of y on x may be written as

Y = mx + c

m & c must be optimum , so that the equation gives, for each value of x, best estimate a linear equation can give for the average value of y. The term, ‘best estimate’ is interpreted in accordance with the principle of least squares, that is to say, m & c will be optimum when the sum of the squares of the deviations of the actual values of y from the line (a).

Thus,

e = y – mx – c

Where e = vertical dispersion of any point in the scatter diagram from the line (a)

e2 = (y – mx – c) 2

Σ e2 = Σ (y – mx – c) 2

Now e2 to be minimum,

69

Σ e 2

= 0 and ∂ Σ e 2

= 0

m ∂c

Or ∂ Σ( y – mx - c) 2

= 0 ∂m

Or Σxy – mΣx2 - cΣx

= 0 …….(i)

again

∂ Σ( y – mx - c) 2

= 0 ∂c

Or Σy – mΣx - cΣ

= 0 …….(ii)

The equations (i) and (ii) are known as normal equations from which m & c can be calculated

Similarly, the line of regression of x and y

X = mty + ct

Can be determined.

Co relation coefficient: - The slopes of the regression lines are called coefficients of regression (m = coefficient of regression of y on x and mt =

70

coefficient of regression of x on y).Its square root (i.e. √ mxmt) is called the coefficient of co-relation, r.

The co-efficient of co-relation lie in between -1 and +1. If r=1 or -1, the sum of the squares of deviations from either line of regression is zero. Consequently each deviation is zero, and all the points lie on both lines of regression. These two lines then coincide, and there is a linear functional relation between the variables x and y, giving perfect correlation. The nearer r2 is to unity, the closer are the points to the lines of regression, and the nearer are these two lines to coincidence. Thus the magnitude of r may be taken as a measure of the degree to which the association between the variables approaches a linear functional relationship. The sign of r is the same as that of the gradients of the lines of regression. Hence r is positive when, on the whole, y increases with x, and negative when y decreases as x increases. When r is zero the variables are usually described as uncorrelated.

Hence

In statistics, linear regression is a regression method that allows the relationship between the dependent variables, Y and independent variables X and a random term ε.

The model can be written as

Y = a + bx + ε

MULTIPLE REGRESSION :-

Regression model which is carried out to established a relationship between two or more independent variable with one dependent variable is called multiple regression and the model can be written as

71

Y= a + b1x1 + b2x2 + b3x3 + ………bnxn + ε

HERE:-

Y = the variable that we are trying to predict

x = the variables that we are using to predict Y

a = the intercept

b = the slope (Regression coefficient)

n = Number of variables

ε = the regression residual

Linear regression models with more than one independent variable are referred to as MULTIPLE LINEAR MODELMULTIPLE LINEAR MODEL , as opposed to simple linear models with one independent variable.

The following notation is used in this work:

y - Dependent variable (predicted by a regression model)

y* - Dependent variable (experimental value)

p - Number of independent variables (number of coefficients)

xi (i=1,2, …p) - ith independent variable from total set of p variables

bi (i=1,2, …p) - ith coefficient corresponding to xi

b0 - intercept (or constant)

k=p+1 - total number of parameters including intercept (constant)

n - number of observations ( experimental data points)

i =1,2 … p - independent variables’ index

j=1,2, … n - data points’ index

Now let us illustrate the classification of regression models with mathematical expressions: Multiple linear model

General formula:

72

y = b0 + b1x1 + b2x2 + … bpxp (1)

y = b0 + ∑i bixi i=1,2,… p (1a)

MAIN OBJECTIVES OF MULTIPLE LINEAR REGRESSION ANALYSIS

Our primary goal is to determine the best set of parameters bi, such that the model predicts experimental values of the dependent variable as accurately as possible (i.e. calculated values yj should be close to experimental values yj* ).

We also wish to judge whether our model itself is adequate to fit the observed experimental data (i.e. whether we chose the correct mathematical form of it).

We need to check whether all terms in our model are significant (i.e. is the improvement in “goodness” of fit due to the addition of a certain term to the model bigger than the noise in experimental data).

DESCRIPTION OF REGRESSION INPUT AND OUTPUT :-

In order to perform a regression analysis we choose from the Microsoft Excel menu*:

Tools Data analysis Regression

Note that data analysis tool should have been previously added to Microsoft Excel during the program

setup (Tools – Add-Ins – Analysis ToolPak).

The pop-up input dialog box is shown on Fig. Elements of this box are described in online help. Most of them become clear in the course of our discussion as well.

The “Input Y range” refers to the spreadsheet cells containing the independent variable y*

and the “Input X range” to those containing independent variables x ( in our example x =

73

x1, x2, x3) (see Table 2). If we do not want to force our model through the origin we leave

the “Constant is Zero” box unchecked. The meaning of “Confidence level” entry will

become clear later. The block “Output options” allows one to choose the content and

locations of the regression output. The minimal output has two parts “Regression

Statistics” and “ANOVA” (Analysis Of Variance). Checking the appropriate boxes in

Sub blocks “Residuals”

Now we are ready to proceed with the discussion of the regression output.

SUMMARY OUTPUT:-

Regression statistics

Multiple R

R Square

Adjusted R Square

Standard Error

Observations

74

ANOVA (analysis of variance)

df SS MS F Significance F

Regression

Residual

Total

Coefficients Standard Error t Stat P-value Lower 95 % Upper 95%

Intercept

X Variable 1

X variable 2

X variable 3

-

X variable n

here

Multiple R = correlation coefficient

R Square = coefficient of determination

Where

R2= SSR/SST= Sum of squares explained by regression/Total sum of squares

Adjusted R square= it represent the proportion of variability of Y explained by the X‘s. R square is adjusted so that model with different number of variables can be compared.

75

Standard error = The standard deviation of the variation of observation around the regression line is estimated by

S ε = √SSE/n-k-1

Where

SSE = Sum of squares error

n = Sample size

k = Number of independent variable in the model

Observations= Number of sample data collected (Sample size)

Residual= The difference between the observed value of the dependent variable (Y) and the predicted value (Y*) is called the residual. Each data point has one residual

Intercept :-

The general meaning of the word intercept is: "y-coordinate of the point where a given line intersects the y-axis".

Two parameters are needed to unambiguously define a straight line, and the other parameter is usually the slope.

76

 The term is most often referring to the intersection of a Least Squares Line (LSL) with the y-axis with the context of Simple Linear Regression (SLR).  Because the LSL embodies the predictions of the model, the intercept is the prediction of the SLR for the value "0" of the predictor x. SLR is often used to describe the evolution of the response variable y when a "control" variable x varies across a range. The intercept of the LSL then answers the question: "What would the value of y be if x were tuned to 0?”

df = degree of freedom

SS = sum of squares explained by regression

MS = mean square

F & Significance F = The F test in the ANOVA table , significance F indicates a linear relationship between Y and at least one of the X’s.

t- stat = The t test of each partial regression coefficient significant t indicates that the variable in question influences the Y response while controlling for other explanatory variables

Confidence or prediction interval of a regression line :-

If you check the option box Prism will calculate and graph either the 95% confidence interval or 95% prediction interval of the regression line. Two curves surrounding the best-fit line define the confidence interval.

Drawing is coming here page 49

The dashed lines that demarcate the confidence interval are curved. This does not mean that the confidence interval includes the possibility of curves as well as straight lines. Rather, the curved lines are the boundaries of all possible straight lines. The figure below shows four possible linear regression lines (solid) that lie within the confidence interval (dashed).

77

Drawing is coming here page no 50

Given the assumptions of linear regression, you can be 95% confident that the two curved confidence bands enclose the true best-fit linear regression line, leaving a 5% chance that the true line is outside those boundaries.

Many data points will be outside the 95% confidence interval boundary .The confidence interval is 95% sure to contain the best-fit regression line. This is not the same as saying it will contain 95% of the data points.

The 95% prediction interval is the area in which you expect 95% of all data points to fall. In contrast, the 955 confidence interval is the area that has a 955 chance of containing the true regression line. This graph shows both prediction and confidence intervals (the curves defining the prediction intervals are further from the regress on line).

Insert drawing here

The analysis of data obtained in between Jan 2009 to Dec 2011 of BF#5 was analyzed. The data was recorded and analyzed in terms of obtaining best fit curve equations.

78

CHAPTER 6

DATA ANALYSIS OF BF # 5

(JANUARY 2009 – DECEMBER 2011)

79

Coke Rate Calculations

MONTH PRODUCTIONCOKE RATE PRODUCTIVITY

CDI RATE HBT

TOP PR.

N/D CAST %

T. D.

MOISTUR %

AVAIL. %

SINTER %

JAN'09 73673 435 1.63 77 996 0.92 0.0 67.0 2.9 97.6 67.6

FEB 71514 418 1.71 101 995 0.89 0.5 69.2 2.9 100.0 65.9

MAR 74175 430 1.64 101 989 0.92 0.9 68.9 4.0 97.8 67.1

APR 73046 434 1.73 99 995 0.89 1.1 71.5 2.6 94.3 68.0

MAY 73711 449 1.66 85 987 0.88 0.5 71.7 2.4 95.8 69.9

JUN 78103 460 1.77 65 973 0.75 2.2 73.8 2.1 98.9 67.9

JUL 76895 478 1.66 51 953 0.74 2.6 70.9 2.0 100.0 68.1

AUG 72762 465 1.58 67 903 0.75 2.1 70.7 1.8 99.5 63.7

SEP 70453 453 1.65 73 942 0.76 2.7 71.1 2.1 95.6 65.4

OCT 73681 470 1.62 66 950 0.82 2.5 69.8 2.6 98.1 59.1

NOV 67481 446 1.58 71 936 0.71 0.5 72.1 2.6 95.4 65.3

DEC 74848 470 1.62 70 926 0.76 1.9 73.1 3.3 99.2 66.7

JAN'10 76663 470 1.68 68 942 0.76 0.5 70.4 3.4 98.7 67.6

FEB 25087 514 1.47 34 921 0.70 1.4 69.3 3.6 54.4 68.2

MAR 76447 471 1.65 60 948 0.64 0.5 72.6 4.4 100.0 66.2

APR 71001 460 1.67 75 921 0.57 0.5 71.8 3.2 95.3 63.2

MAY 77684 467 1.68 71 949 0.68 1.5 71.8 3.2 100.0 65.4

JUN 77122 458 1.72 74 945 0.74 1.4 70.1 2.7 100.0 63.8

JUL 72310 475 1.66 57 925 0.70 0.5 70.7 2.7 94.5 66.7

AUG 79099 451 1.71 71 918 0.71 0.4 71.1 2.9 100.0 63.4

SEP 77033 472 1.73 56 931 0.72 0.0 72.1 3.8 99.3 68.3

OCT 71359 455 1.60 64 913 0.74 0.5 69.9 3.7 96.4 65.0

NOV 71086 446 1.62 61 905 0.75 0.0 70.4 4.0 98.1 65.4

DEC 80271 467 1.74 60 897 0.71 0.5 71.6 3.8 100.0 64.7

JAN' 11 73585 465 1.64 71 912 0.74 0.0 72.6 3.7 97.3 67.0

FEB 64537 490 1.55 59 928 0.78 0.0 71.9 4.2 100.0 65.5

MAR 77053 437 1.69 87 934 0.70 1.4 66.9 3.3 100.0 64.1

APR 61840 440 1.55 94 939 0.75 0.0 64.2 2.8 89.2 64.9

MAY 64643 484 1.50 54 869 0.74 0.0 73.0 2.4 93.0 67.0

JUN 61168 500 1.47 41 871 0.69 0.0 71.8 2.3 93.3 65.0

JUL 65915 471 1.43 60 920 0.76 0.0 74.4 5.7 100.0 64.1

AUG 68618 483 1.48 41 929 0.76 0.0 71.7 4.9 100.0 67.7

SEP 64343 461 1.51 65 920 0.81 0.0 70.7 5.5 94.2 66.2

OCT 64783 480 1.46 49 914 0.83 0.0 70.0 6.6 95.8 67.8

NOV 67007 446 1.56 56 884 0.77 0.0 74.3 3.8 96.1 65.2

DEC 74508 457 1.61 82 918 0.77 0.0 74.6 3.5 100.0 66.0

     

80

coke ash

Si in HM

S in HM

Slag rate

-5mm in sinter O2 VOL.

BLAST PR.

Total slag I/ore Sinter

16.9 0.61 0.026 388 8.1 1.18 2597 2.03 0 40599.0 84885.016.7 0.58 0.026 392 8.1 1.35 2724 2.03 0 41464.0 81046.016.8 0.65 0.025 391 8.1 1.33 2697 2.02 0 42025.0 85636.016.9 0.62 0.026 391 7.4 1.35 2672 2.01 28586 39473.0 84072.016.8 0.64 0.024 401 5.6 1.21 2652 1.93 29557 37854.0 87947.016.3 0.61 0.029 407 6.8 0.96 2721 1.94 31749 42618.0 90109.016.4 0.62 0.025 410 7.5 0.88 2627 1.90 31556 41673.0 89058.016.5 0.63 0.027 395 5.1 0.90 2627 1.90 28741 43465.0 76340.016 0.62 0.026 397 5 1.18 2638 1.91 27990 40131.0 75737.0

15.8 0.66 0.03 398 5 1.09 2665 1.97 29298 49745.0 71733.015.7 0.67 0.032 434 4.9 1.15 2625 1.92 27076 39109.0 73606.015.6 0.67 0.028 402 4.9 1.18 2548 1.98 30069 42057.0 84361.016 0.65 0.026 397 5.6 0.96 2715 1.98 30418 42165.0 88161.0

16.2 0.9 0.024 400 4.9 1.28 2435 1.87 10045 14360.0 30744.016.4 0.65 0.032 393 4.8 1.11 2672 1.90 30065 42783.0 86907.017.4 0.57 0.035 395 5.2 0.94 2638 1.83 28033 39000.0 78348.016.9 0.58 0.03 404 5.7 1.47 2613 1.93 31372 40633.0 84521.016.1 0.56 0.032 394 5.6 1.48 2700 1.93 30400 44520.0 81854.015.8 0.62 0.034 394 6.6 1.39 2579 1.88 28515 39240.0 79459.016.2 0.63 0.028 384 5.3 1.38 2690 1.94 30405 47955.0 83479.016 0.66 0.034 398 5.4 1.38 2737 2.00 30644 40532.0 87397.016 0.69 0.029 386 5.2 1.13 2592 1.98 27571 40793.0 76363.0

16.2 0.64 0.029 396 3.9 1.17 2627 1.96 28155 40728.0 77040.016.1 0.7 0.027 400 4.8 1.21 2715 1.93 32094 47433.0 86975.016.1 0.71 0.03 402 4.8 1.21 2645 1.95 29549 40793.0 83487.016.7 0.77 0.032 408 4.5 1.38 2631 1.99 26322 36723.0 70430.016.1 0.66 0.028 391 4.4 1.22 2662 1.93 30143 45154.0 80685.016.4 0.64 0.028 400 4.5 1.15 2464 1.91 0 35708.0 65998.016.3 0.73 0.029 403 4.7 1.03 2344 1.95 0 34677.0 70433.016.1 0.79 0.028 398 6.9 1.27 2529 1.81 0 37020.0 68844.016 0.75 0.031 398 5.1 1.22 2559 1.93 0 39650.0 70661.0

15.7 0.67 0.035 391 5.8 1.13 2530 1.96 0 37161.0 77820.015.8 0.73 0.032 402 6 1.18 2481 1.97 0 35817.0 70303.015.9 0.75 0.028 401 5.9 1.05 2618 2.03 0 34526.0 72711.015.9 0.68 0.03 397 5.2 1.12 2574 1.95 0 40233.0 75395.016.3 0.64 0.031 403 5.3 0.86 2683 1.99 0 43377.0 84057.0

SUMMARY OUTPUT

Regression Statistics

81

Multiple R 0.930297

R Square 0.865453Adjusted R Square 0.803786Standard Error 8.861407

Observations 36

ANOVA

df SS MS F Significance F

Regression 11 12122.36 1102.033 14.03425 6.62E-08

Residual 24 1884.589 78.52454

Total 35 14006.95

CoefficientsStandard

Error t Stat P-valueLower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept 129.3861 134.92 0.958984 0.347129 -149.075 407.8473 -149.075 407.8473

CDI RATE -0.72929 0.167646 -4.3502 0.000217 -1.0753 -0.38329 -1.0753 -0.38329

HBT -0.0088 0.100632 -0.08747 0.931026 -0.2165 0.198893 -0.2165 0.198893

TOP PR. -25.4436 34.22111 -0.74351 0.464392 -96.0726 45.18526 -96.0726 45.18526

N/D CAST % 6.583495 3.0099 2.18728 0.0387 0.371366 12.79562 0.371366 12.79562

T. D. -0.20349 0.925757 -0.21981 0.827878 -2.11416 1.707177 -2.11416 1.707177

MOISTUR % -1.83099 2.021704 -0.90567 0.374115 -6.00358 2.341601 -6.00358 2.341601

AVAIL. % -0.25451 0.323976 0.785581 0.4398 -0.41414 0.923163 -0.41414 0.923163

SINTER % -1.34022 1.092814 1.226392 0.231948 -0.91524 3.595677 -0.91524 3.595677

coke ash 9.653116 4.896655 1.971369 0.060317 -0.45308 19.75931 -0.45308 19.75931

Si in HM 163.8273 48.55812 3.37384 0.002514 63.6083 264.0464 63.6083 264.0464

S in HM 1599.91 886.5714 1.804604 0.083701 -229.883 3429.704 -229.883 3429.704

RESIDUAL OUTPUT

Observation Predicted COKE RATE Residuals

82

1 442.6613152 -7.249835162

2 419.3055773 -1.383864783

3 431.6698545 -2.100412098

4 435.3102957 -1.446702858

5 443.8910714 5.382374883

6 470.3640192 -10.11281246

7 480.4651703 -2.553732673

8 465.5851818 -0.410346546

9 457.0674038 -3.885850157

10 462.2218798 7.722882106

11 459.3872694 -13.38726943

12 462.3480932 7.297054251

13 453.0491128 16.68204827

14 513.9758029 0.508590195

15 471.443056 -0.936064747

16 461.3724891 -1.03484496

17 460.9215318 6.201685317

18 447.6979254 10.66674359

19 468.4095556 6.407205612

20 449.6322471 1.751461876

21 474.1797047 -1.680905463

22 463.5979315 -8.182356732

23 456.7569073 -10.75690728

24 466.3598878 1.081653994

25 463.1666948 2.172708626

26 488.1394937 2.121906783

27 449.6953998 -12.73642347

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28 433.4243702 6.083165348

29 480.6622838 3.071453822

30 495.9624611 3.955796829

31 470.9018472 -0.007513605

32 481.6204983 1.532610191

33 464.6644947 -3.371113911

34 474.5600101 5.439989859

35 463.8210944 -17.82109442

36 446.0212808 10.97871921

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.85085489

R Square 0.72395404Adjusted R Square 0.5399234

Standard Error 0.06048566

Observations 36

ANOVA

df SS MS FSignificance

F

Regression 14 0.20149015 0.01439215 3.93387776 0.00239511

Residual 21 0.07682883 0.00365852

Total 35 0.27831897

CoefficientsStandard

Error t Stat P-value Lower 95% Upper 95%Lower 95.0%

Upper 95.0%

Intercept 1.37896154 0.99062558 1.39201084 0.17848733 -0.6811571 3.4390802-

0.6811571 3.4390802

CDI RATE 0.00074778 0.00123371 0.60612455 0.5509283 -0.0018179 0.00331343-

0.0018179 0.00331343

HBT 0.00110688 0.00074004 1.49570476 0.14960835 -0.0004321 0.00264589-

0.0004321 0.00264589

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TOP PR. 0.49226744 0.2504888 -1.9652273 0.06275324 -1.0131874 0.02865253-

1.0131874 0.02865253

N/D CAST % -0.0016111 0.02093055 0.0769738 0.93937305 -0.0419164 0.04513857-

0.0419164 0.04513857

T. D. 0.00674574 0.00641284 1.0519116 0.30479451 -0.0065905 0.02008198-

0.0065905 0.02008198

MOISTUR % 0.01550212 0.01481501 -1.046379 0.30728136 -0.0463116 0.01530739-

0.0463116 0.01530739

AVAIL. % 0.00204117 0.00223371 0.91380554 0.37119215 -0.0026041 0.00668642-

0.0026041 0.00668642

SINTER % 0.00554951 0.00769542 0.72114477 0.47877278 -0.010454 0.02155302 -0.010454 0.02155302

coke ash -0.0267085 0.03458664 -0.7722208 0.44858765 -0.0986354 0.04521833-

0.0986354 0.04521833

Si in HM -0.5012955 0.36189347 -1.3852019 0.18052996 -1.2538942 0.25130314-

1.2538942 0.25130314

S in HM -7.3648265 6.28478999 -1.1718493 0.25438152 -20.434763 5.70510974-

20.434763 5.70510974

Slag rate -0.0013976 0.00148291 -0.9424589 0.35667454 -0.0044815 0.0016863-

0.0044815 0.0016863

-5mm in sinter -0.0077332 0.01382738 -0.5592662 0.58189621 -0.0364888 0.02102242-

0.0364888 0.02102242

O2 0.10117089 0.07147468 1.4154787 0.17158822 -0.0474688 0.24981063-

0.0474688 0.24981063

Productivity=1.37+0.00074*CDI rate+0.0011*HBT+0.492*TP-0.0016*ND cast+0.006745*TD +0.0155*Moist+0.00204*Avail

+0.0055*Sinter %-0.026*coke ash-0.501*Si-7.364*S-0.00139*Slag rate -0.0077*(-5mm) in sinter+0.10*O2 enrich

RESIDUAL OUTPUT

Observation Predicted PRODUCTIVITY Residuals1 1.634765807 -0.001317735 CDI 802 1.707622245 0.005369994 HBT 9503 1.638384391 0.001615609 TP 0.84 1.710231984 0.021418597 ND 0.25 1.704010978 -0.044010978 TD 706 1.704410424 0.061307479 Moist 3.57 1.665223222 -0.001585482 Avail 998 1.61428658 -0.031557775 Sinter 659 1.707518439 -0.059186587 Coke ash 15

10 1.579324516 0.045349555 Si 0.711 1.601840042 -0.020743565 S 0.02512 1.658923739 -0.039573227 Slag rate 38013 1.651907587 0.028092413 5mm in sinter 714 1.452712462 0.021064507 O2 115 1.680296797 -0.030296797

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16 1.648805962 0.01719001417 1.731549677 -0.050841774 1.3559618 1.717815762 0.00218423819 1.654680566 0.00100031920 1.697418409 0.01390328421 1.638613989 0.09138601122 1.594612534 0.00738999723 1.600007053 0.02073154324 1.600785768 0.13571928325 1.596351243 0.03965262626 1.521406241 0.0244642227 1.672813427 0.01695460928 1.610906217 -0.06283082829 1.523056413 -0.02305641330 1.522475081 -0.05727914331 1.536340645 -0.11027889832 1.563011501 -0.07844820733 1.484590178 0.02728467634 1.453722198 0.00627780235 1.552329018 0.00767098236 1.595020347 0.014979653

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.931077R Square 0.866905Adjusted R Square 0.788258Standard Error 9.205377Observations 36

ANOVA df SS MS F Significance F

Regression 13 12142.693 934.053 11.02271 8.472E-07Residual 22 1864.2572 84.739Total 35 14006.95

CoefficientsStandard

Error t Stat P-valueLower 95% Upper 95%

Lower 95.0%

Upper 95.0%

Intercept 142.7239 149.98251 0.9516 0.351637 -168.3208 453.768575 -168.3208 453.768575

CDI RATE -0.72509 0.1860483-

3.89732 0.000774-

1.1109311 -0.3392499 -1.1109311 -0.3392499

HBT -0.00065 0.10894 0.00595 0.995305-

0.2252793 0.22657601 -0.2252793 0.22657601TOP PR. -24.7946 37.984632 - 0.520678 - 53.9806976 -103.56991 53.9806976

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0.65275 103.56991N/D CAST % 6.736699 3.1607123 2.13139 0.044474 0.1817829 13.2916152 0.18178289 13.2916152

T. D. -0.12888 0.9757-

0.13209 0.896118-

2.1523533 1.89460251 -2.1523533 1.89460251

MOISTUR % -2.1779 2.2246691-

0.97897 0.338236-

6.7915768 2.43578592 -6.7915768 2.43578592

AVAIL. % -0.2775 0.3399446 0.8163 0.423077-

0.4275035 0.98250021 -0.4275035 0.98250021

SINTER % -1.47525 1.1695306 1.26141 0.220374-

0.9502033 3.9007128 -0.9502033 3.9007128

coke ash 9.519473 5.2123117 1.82634 0.081401-

1.2901995 20.3291463 -1.2901995 20.3291463Si in HM 171.165 53.508274 3.19885 0.004143 60.195588 282.134324 60.1955885 282.134324S in HM 1692.455 942.08387 1.7965 0.08616 -261.3071 3646.21764 -261.3071 3646.21764

Slag rate 0.104009 0.218155-

0.47677 0.63823-

0.5564346 0.34841682 -0.5564346 0.34841682

-5mm in sinter 0.401844 2.1025376-

0.19112 0.850182-

4.7622396 3.95855247 -4.7622396 3.95855247325.72 433.564

Coke rate =142.72-0.725*CDI-0.000648*HBT-24.79*Top Pr+6.736*ND cast-0.1288*TD-2.1778*Moist-0.2775*Avail-1.475*Sinter+9.519*Coke ash+171.16*Si+1692.16*S+0.1040*Slag rate+0.4018*(-5mm) in sinter

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RESIDUAL OUTPUTObservation Predicted COKE RATE Residuals CDI 90

1 442.7092287 -7.297748601 HBT 9502 418.8995675 -0.977854985 TP 0.853 431.4737909 -1.904348525 ND 0.24 436.0589179 -2.195325141 TD 705 444.4326859 4.840760375 Moist 56 470.1357647 -9.884557942 Avail 997 479.0182316 -1.106793921 Sinter 65

8 465.8722207 -0.697385464Coke ash 16.5

9 457.6477007 -4.466147045 Si 0.5510 462.3671864 7.577575498 S 0.025

11 456.5600306 -10.56003056Slag rate 380

12 462.7569663 6.888181207 5mm 713 453.1066994 16.6244616114 514.291177 0.1932161115 472.3413526 -1.83436132116 461.0551817 -0.71753759917 460.0471449 7.0760722818 447.877839 10.4868299319 468.753571 6.06319017920 450.6004193 0.78328970921 474.8788401 -2.38004085322 464.664675 -9.24910023623 456.82048 -10.8204799624 465.9825379 1.45900383125 463.4086898 1.93071356326 488.1993405 2.06205989227 450.5412624 -13.5822861528 432.8393402 6.6681954129 480.7753764 2.95836124530 495.7084389 4.20981897831 470.9804303 -0.08609670932 482.5701043 0.5830042633 463.9448886 -2.6515078234 473.462418 6.53758200135 463.7472297 -17.7472296636 445.7834836 11.21651642

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Chapter 7

SUGGESTIONS FOR IMPROVING COKE RATE & PRODUCTIVITY OF BFs AT BSP

Suggestions based on Data Analysis :

The data of BF # 5 collected during the study period was analyzed using Multiple Linear Regression Technique and a model was developed to predict the coke rate and productivity for a given set of data. The regression analysis was done with the help of standard software using Microsoft Excel and the formula for coke rate and productivity calculation was developed. The formula obtained for coke rate and productivity are as follows:

The equations obtained as above are of the linear type and are showing relationship between (coke rate and parameters) & (productivity and process variable). These are in good agreement with theory As for example, theory says that the coke rate should go down if the CDI rate is increased. This fact is validated by the coke rate formula shown above. The same is true in case of productivity which should increase with a corresponding increase in CDI rate. In the same way, other factors also influence the coke rate and productivity.

If the coke rate formula developed above is looked into carefully, we would observe that the factors like CDI rate, HBT, Top pressure, Tapping duration,

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Productivity=1.37+0.00074*CDI rate+0.0011*HBT+0.492*TP-0.0016*ND cast+0.006745*TD+ 0.0155*Moist+0.00204*Avail+0.0055*Sinter %-0.026*coke ash-0.501*Si-7.364*S- 0.00139*Slag rate-0.0077*(-5mm) in sinter+0.10*O2 enrich

Coke rate=142.72-0.725*CDI-0.000648*HBT-24.79*Top Pr+6.736*ND cast-0.1288*TD- 2.1778*Moist- 0.2775*Avail-1.475*Sinter+9.519*Coke ash+171.16*Si+1692.16*S+ 0.1040*Slag rate + 0.4018*(-5mm) in sinter

Moisture, Availability, % Sinter in burden are positive factors. That means that with their increasing values, the coke rate will be decreases. Similarly factors like not dry cast, coke ash, % Si in hot metal, % S in hot metal, slag rate and -5mm in sinter are negative ones because with their increasing values, coke rate will go up.

From the above coke rate formula, it is also observed that out of the positive factors, the highest slope value is of top pressure and then that of moisture, sinter %, CDI rate, Availability and HBT etc. This indicates that in case of BF # 5 operation, coke rate can be significantly decreased by optimizing the top pressure in the furnace.

Similarly, in the case of Productivity formula CDI rate, HBT, Top pressure, tapping duration, moisture, Availability, Sinter % and O2 enrichment etc are positive factors i.e productivity goes up with their increasing value and not dry cast, coke ash, % Si & S in hot metal, slag rate, -5 mm in sinter are negative factors.

It is also seen from the productivity formula that the highest slope is of Top pressure (positive factor) and % Si & S in hot metal (negative factors). This indicates that the productivity of BF # 5 can be significantly increased if top pressure operation in the furnace is optimized along with Si, S in hot metal.

The line fit graphs of coke rate vs various independent variables and Productivity vs different independent variables are as follows:.

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Fig Showing decreasing coke rate with increasing Sinter %

Fig Showing decreasing coke rate with increasing CDI rate

Fig Showing decreasing coke rate with increase in Top pressure

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Fig Showing increase in coke rate with increase in coke ash %

Fig Showing decrease in coke rate with increasing tapping duration

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Fig Showing increase in coke rate with increase in slag rate

Fig Showing decrease in coke rate with increasing moisture %

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Fig Showing decreasing coke rate with increasing availability

Fig Showing increase in coke rate with increasing Si in hot metal

Fig Showing increase in coke rate with increase in S in hot metal

Fig Showing Decrease in coke rate with increase in HBT

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Fig Showing increase in coke rate with increase in Not dry cast

Fig No Showing increasing coke rate with increase in -5mm in sinter

Fig Showing increase in productivity with increase in coke rate

95

Fig Showing increase in productivity with increase in HBT

Fig showing increase in productivity with increase in Tapping duration

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The coke rate and productivity formula that has been devised is very helpful in calculating the variation in it with a corresponding change in other parameters.

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As for example, coke rate and productivity are calculated based on a set of data considering:

CDI rate: 80 kg/thm,

HBT: 950 deg C

Top pressure: 0.8 kg/cm2

Not dry cast : 0.2 %

Tapping duration: 70 %

Moisture: 3.5 t/hr

Availability: 99 %

Sinter: 65 %

Coke ash: 15 %

Si in hot metal: 0.6 %

S in hot metal: 0.025 %

Slag rate: 380 kg/thm

-5mm in sinter: 7%

O2 enrichment: 1%

Then the coke rate and productivity obtained from the above two formula is 439 kg/thm and 1.4 t/m3/day. Now, if suppose ash in coke goes up by 1 %, then from the above formula the coke rate will be 449 kg/thm and the productivity 1.38 t/m3/day. Thus there would be an increase of 10 kg/thm in coke rate and a decrease of 0.02 t/m3/day in productivity for a 1% increase in coke ash. For another example, if Si in hot metal goes up by 0.1 %, then in the case of BF # 5, the coke rate will be 456 kg/thm i.e. an increase of 17 kg/thm in coke rate and the productivity will be 1.35 t/m3/day i.e. a decrease of 0.05 t/m3/day in productivity.

Thus this model is very helpful in knowing the changes in coke rate and productivity for any change in other factors affecting it.

This model can also be used to know the changes required in other factors to keep the coke rate and productivity unchanged for a certain change in one factor. For example, the coke rate increased by about 10 kg/thm for 1% increase in coke ash. Now to keep the coke rate unchanged at a figure of 439 kg/thm, what should

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be the change in other factors can be predicted by this model. The model predicts that the coke rate can be kept unchanged by increasing sinter % in burden or keeping the Si in hot metal to around 0.55 % depending upon the furnace operating conditions.

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CONCLUSION

“A blast furnace is a giant chemical reactor in which 2758 chemical reactions takes place simultaneously more or less out of control”.

So it is very difficult to precisely predict values of critical parameters such as coke rate and productivity with the help of personal experience or using any mathematical model. But in this project work, by regression techniques, data were analyzed and the two models were developed to help BF operators. In today’s circumstances, Bhilai Steel Plant is facing severe coke crisis and is meeting its requirement by procuring coke from different sources at a very high price with a remarkable degradation in other raw materials quality, such models will prove to be very helpful to BF operators. As a Blast Furnace operator, we know these facts qualitatively but the above two models will tell us in quantitative terms the exact changes that would take place for any change in dependent factors.

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