A

Summer Internship Project Report

On

“Slag Handling System”

&

“Forecasting the Price and Production of Steel”

in the partial fulfillment of the Degree of

Master of Business Administration

Submitted By

Zorawar Singh Nandwal

MBA 2nd Year & Roll No:401257013

Batch: 2015-17

Under the Guidance of

Mr. Vikas Aggarwal

& Mr. Sambit Mishra

(ED & CTO Office, Jindal Steel & Power Ltd.)

L.M. Thapar School of Management (Thapar University, Patiala)

Dera Bassi Campus, Mohali - 140507

2016

2

A

Summer Internship Project Report

On

“Slag Handling System”

&

“Forecasting the Price and Production of Steel”

in the partial fulfillment of the Degree of

Master of Business Administration

Submitted By

Zorawar Singh Nandwal

MBA 2nd Year & Roll No:401257013

Batch: 2015-17

Under the Guidance of

Mr. Vikas Aggarwal

& Mr. Sambit Mishra

(ED & CTO Office, Jindal Steel & Power Ltd.)

L.M. Thapar School of Management (Thapar University, Patiala)

Dera Bassi Campus, Mohali - 140507

2016

3

Declaration

I hereby declare that the project work entitled “Slag Handling System” & “Forecasting the Price

and Production of Steel” is a record of work done under the guidance of Mr. Vikas Aggarwal,

Manager – Best Practices Technology Group and Mr. Sambit Mishra, Manager – Best Practices

Technology Group at JSPL, Angul. This project work is submitted in the fulfillment of the

requirement of academic credit for Summer Internship in Masters of Business Administration at

LM Thapar School of Management.

Place: Dera Bassi Zorawar Singh Nandwal

Date: 22nd August 2016 401257013

4

Certificate

5

Acknowledgement

I would like to express my gratitude to all the workforce at JSPL, Angul who have guided and

advised me through the course of my internship. I am indebted to my mentors Mr. Vikas Aggarwal

and Mr. Sambit Mishra for their constant support and tutelage during my internship. Also I Would

like to thank Dr. Rudra Rameshwar (Assistant Professor, LM Thapar School of Management) for

his constant support for the initiation, duration and completion of my training. I would take this

opportunity to thank Mrs. Sonia Garg who through her course of Managerial Accounting made my

basics clear which helped me in the Slag Handling Project.

Under the constant tutelage and advise from the faculty at LM thapar school of management, I was

able to witness the steel industry from a management perspective and was able to apply the skills I

have learnt during the course of my degree.

Zorawar Singh Nandwal

Roll no.- 401257013

LM Thapar School of Management

6

Abstract

Slag Handling system at JSPL is handled by Ecomaister Beads India. The process involves

atomizing and crushing the slag. Although since the inception, the operation has largely been

expensive for JSPL since most of the slag was crushed which was costlier as compared to

Atomizing. This project was initiated to find out the bottlenecks and the reasons due to which it

was non-profitable. Also the authorities were seeking alternatives to the present operation. In this

project, the main focus was to find the most profitable and beneficial way to process the slag.

Forecasting projects require a lot of data. This project involved forecasting the production and

price of steel in India. Forecasting technique of regression is used in this project to forecast the

price and production of steel. Also trend analysis is performed month wise depicted through a

graph.

7

Contents Certificate ...................................................................................................................................................................... 4

Abstract .......................................................................................................................................................................... 6

About the Organization ............................................................................................................................................... 10

Jindal Steel and Power Ltd. ..................................................................................................................................... 10

Company Profile ................................................................................................................................. 10

JSPL Vision ........................................................................................................................................ 12

JSPL Mission ...................................................................................................................................... 12

JSPL Core Values ............................................................................................................................... 12

Products ................................................................................................................................................................... 13

Business ................................................................................................................................................................... 14

JSPL Angul .................................................................................................................................................................. 14

Technology .............................................................................................................................................................. 14

Project Highlights .................................................................................................................................................... 15

PROJECT-I .................................................................................................................................................................. 17

Methodology ................................................................................................................................................................ 18

Data Collection ............................................................................................................................................................ 19

Data Analysis & Discussion ..................................................................................................................................... 20

Findings & Suggestions ........................................................................................................................................... 28

Alternatives ......................................................................................................................................... 28

Summary of Analysis and Suggestions .................................................................................................................... 30

Conclusions & Recommendation ............................................................................................................................. 32

References ................................................................................................................................................................ 34

Project-II ...................................................................................................................................................................... 35

Forecasting the Production and Price of Steel in India ............................................................................................ 35

Steelmaking Process ............................................................................................................................ 36

Methodology ............................................................................................................................................................ 37

Data Analysis and Discussion ................................................................................................................................. 40

Correlation Analysis ........................................................................................................................... 42

Forecasts Made (Findings) ...................................................................................................................................... 46

8

List of Tables

Table-1: Slag Crushing Rate with respect to PS Ball Generation

Table-2: Calculation of Rate per Ton

Table-3: Net Impact of Slag Charges per Ton of Finished Steel

Table-4: Net Impact of Slag Charges per Ton of Finished Steel

Table-5: Cycle Time

Table-6: Kress Maintenance Data

Table-7: Alternatives

Table-8: Alternatives

Table-9: Alternatives

Table-10: Alternatives

Table-11: Comparison with other vendors

Table-12: Eco-Maister Yes or No?

Table-13: Pros & Cons of the Present Contract

Table-14: Options with the present Contract

Table-14: Steel Imports

Table-15: Steel WPI

Table-16: Steel Production

Table-17: Correlation Analysis of Price

Table-18: Regression Analysis of Price

Table-19: Correlation Analysis of Production

Table-20: Regression Analysis of Production

Table-21: Month-wise Steel WPI (2006)

Table-22: Moth-wise Steel Production (2006)

Table-23: Model for Forecasting Price

Table-24: Model for Forecasting Production

9

List of Graphs

Graph-1: Percentage of PS Ball Generation

Graph-2: Rate per Ton of Liquid Steel Produced

Graph-3: Trend Analysis of Steel Price

Graph-4: Trend Analysis of Steel Production

List of Figures

Figure-1: JSPL Plants in India

Figure-2: Products by JSPL

Figure-3: JSPL Plants State-wise

Figure-4: Kress Carrier

Figure-5: Steel Making Process

10

About the Organization

Jindal Steel and Power Ltd.

Company Profile

With its timeless business philosophy JSPL is primed to not merely survive but win in a

marketplace marked by frenetic change. Indeed, the company’s scorching success story has been

scripted essentially by its resolve to innovate, set new standards, enhance capabilities, enrich lives

and to ensure that it stays true to its haloed value system. Not surprisingly, the company is very

much a future corporation, poised to become the most preferred steel manufacturer in the country.

JSPL is an industrial powerhouse with a dominant presence in steel, power, mining and

infrastructure sectors. Part of the US $ 18 billion OP Jindal Group this young, agile and responsive

company is constantly expanding its capabilities to fuel its fairy tale journey that has seen it grow

to a US $ 3.3 billion business conglomerate. The company has committed investments exceeding

US $ 30 billion in the future and has several business initiatives running simultaneously across

continents.

Led by Mr Naveen Jindal, the youngest son of the legendary Shri O.P. Jindal, the company

produces economical and efficient steel and power through backward and forward integration.

From the widest flat products to a whole range of long products, JSPL today sports a product

portfolio that caters to markets across the steel value chain. The company produces the world's

longest (121-meter) rails and it is the first in the country to manufacture large-size parallel flange

beams.

JSPL operates the largest coal-based sponge iron plant in the world and has an installed capacity

of 3 MTPA (million tonnes per annum) of steel at Raigarh in Chhattisgarh. Also, it has set up a

0.6 MTPA wire rod mill and a 1 MTPA capacity bar mill at Patratu, Jharkhand, a medium and

light structural mill at Raigarh, Chhattisgarh and a 2.5 MTPA steel melting shop and a plate mill

to produce up to 5.00-meter-wide plates at Angul, Odisha.

An enterprising spirit and the ability to discern future trends have been the driving force behind

the company's remarkable growth story. The organisation is wedded to ideals like innovation and

11

technological leadership and is backed by a highly driven and dedicated workforce of 15000

people.

JSPL has been rated as the second highest value creator in the world by the Boston Consulting

Group, the 11th fastest growing company in India by Business World and has figured in the Forbes

Asia list of Fab 50 companies. It has also been named among the Best Blue Chip companies and

rated as the Highest Wealth Creator by the Dalal Street Journal. Dun & Bradstreet has ranked it

4th in its list of companies that generated the highest total income in the iron and steel sector.

Alongside contributing to India's growth story the company is driving an ambitious global

expansion plan with its sights set on emerging as a leading transnational business group. The

company continues to capitalise on opportunities in high growth markets, expanding its core areas

and diversifying into new businesses. In Oman (Middle East), the company has set up a US $ 500

million, 1.5 MTPA gas-based Hot Briquetted Iron (HBI) plant. It has now added a 2 MTPA

integrated steel plant.

In Africa, the company has large mining interests in South Africa, Mozambique, Namibia,

Botswana and Mauritania and is expanding into steel, energy and cement. In Australia, the

company is investing in greenfield and brownfield resource sector companies and projects to

supplement its planned steel and power projects in India and abroad.

FIGURE-1

12

In Indonesia, the company has invested on the development of two greenfield exploration assets.

It is also exploring investment opportunities in the power and infrastructure sector in Indonesia.

The company endeavours to strengthen India's industrial base by aiding infrastructural

development, through sustainable development approaches and inclusive growth. It deploys its

resources to improve infrastructure, education, health, water, sanitation, environment and so on in

the areas it operates in. It has won several awards for its innovative business and social practices.

JSPL Vision

To be a globally admired organisation that enhances the quality of life of all stakeholders through

sustainable industrial and business development.

JSPL Mission

We aspire to achieve business excellence through:

The spirit of entrepreneurship and innovation

Optimum utilization of resources

Sustainable environment friendly procedures and practices

The highest ethics and standards

Hiring, developing and retaining the best people

Maximizing returns to stakeholders

Positive impact on the communities we touch

JSPL Core Values

Passion for People

Ownership

Sustainable Development

Sense of Belonging

Integrity

Business Excellence

13

Loyalty

Products

The following figure depicts the different products produced by JSPL.

FIGURE-2

14

Business

JSPL has its business in India as well as in other countries. In India it has plants in Patratu,

Raigarh, Angul, Tensa, Raipur, Barbil, Godda & Asanboni.

It has its international plants in Oman, Australia and Indonesia.

JSPL Angul

Expanding its reach in the domestic market, the company has made considerable investments in

various parts of Odisha. It invested US $ 6 billion in the state for steel production and power

generation. The then proposed steel plant to be set up in Odisha will produce 12.5 MTPA steel and

generate 2600 MW of power in phases.

The company set up a 6 MTPA integrated steel plant at Angul. A 2.5 MTPA steel melting shop

(SMS) has been commissioned. The project is in a fast-track mode, with the 1.5 MTPA plate mill

and an 810 MW captive power plant already commissioned. The plate mill is capable of producing

5-meter-wide plates, making it the widest to be ever produced in the country.

Technology

The DRI-BF-EAF route technology would be adopted for steel production. The DRI plant has a

unique feature of using syn gas from the coal gasification plants as reductant. It is being used for

the first time in the world and has the advantage of using high ash coal which is predominantly

available in the vicinity of the project site. The company has signed an agreement with Lurgi

Technology Company- South Africa, for providing technology for coal gasification.

FIGURE-3

15

The major facilities at the plant include:

Coal washery

Sinter plant

Pellet plant

Coke oven and by-product plant

Coal gasification plant

DRI plant and blast furnace

Steel melting shop

Slab caster

Plate mill and hot strip mill

Oxygen plant

Lime and dolomite plant

Power plant

Project Highlights

The proposed coal gasification technology to be used in this plant offers a practical means of

utilizing indigenous coal for meeting stringent environmental control requirements.

Work is in progress for the establishment of:

o Coal gasification plant to produce 225,000 nm3/hr of syn gas

o DRI plant of 2 MTPA capacity

o Promotion of small-scale industries in and around Angul by giving adequate support with respect

to land, power and buying most of their products for their end-use in the plant (like aggregates,

bricks etc.)

The coal gasification plant is in final stages of commissioning; this marks the completion of 1.5

MTPA integrated facilities of the first phase.

For the next phase, further construction and infrastructure development activities are in advanced

stages. Area grading, soil investigation and various other civil jobs are under progress at site.

16

The company has partnered with several companies of international repute for the purpose of

technology supply and key equipment, detailed engineering, procurement of other equipment,

construction phase, manpower supply and project management services. More than 350

companies, ranging from the biggest international players to the regional vendors are partners in

this endeavor.

17

PROJECT-I

Analyzing the existing slag handling contract with EcoMaister beads India and performing

a cost analysis to suggest alternatives to make the operation more profitable for JSPL

EcoMaister Beads India(EBI) is Subsidiary of EcoMaister Korea. JSPL and EcoMaister Beads

India came into a contract in August 20XX. The contract came into being to address to the Slag

Handling operations of Steel Melting Shop at JSPL. The agreement for processing of the Electric

Arc Furnace & LF Slag at Jindal Steel & Power Limited, Angul through Slag Atomizing

Plant(SAP) and Slag Crushing Plant(SCP).

Under the contract, EBI was required to convert 60% of slag into Precious Slag Balls (PS Balls)

& 40 % of slag into Crushed Slag.

According to the contract, JSPL would pay ₹225/ton of Slag Atomized and ₹350/ton of Slag

Crushed and after Atomizing EBI pays ₹100/ton as royalty to JSPL. These rates were applicable

irrespective of the percentage of Slag Atomized and Crushed.

Keeping the variation of Atomizing and Crushing in mind, JSPL and EBI made changes to the

existing contract of payments and changed the cost according to the percentage of Crushing done.

With the changes in the Crushing Rate it was expected that the expenses would fall down. The

table below shows the new Crushing Rate:

But the inconsistent atomizing and crushing always pushed the expenses towards the higher end.

Following this, management decided to form a committee to find out the reasons for the increased

Table-1

18

expenses and inability of EBI to perform the operations. Also it required the committee to

recommend whether to continue with PS Ball generation concept or get refund back from the

contractor.

Methodology

The first step in this project was to study and understand the contract completely so as to be up to

speed when required. Few major points under this contract were:

60% Electric Arc Furnace(EAF) Slag to be Atomized and 40% EAF Slag to be Crushed at

a cost as per the contract

JSPL shall pay ₹350/ton of Slag Crushed and ₹225/ton for slag Atomized.

Later the contract was modified and under which Crushing Rates varied in regards to PS

Ball generation

As per the Contract, EBI was supposed to Atomize 60% of slag and crush the remaining 40%. But

since the inception of this contract only 4% of slag was Atomized and the remaining 96% was

crushed which increased the expenses of JSPL.

0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

14%

22%

17%

4% 3%0% 0% 0% 0%

8%

2% 0%0%

5%

10%

15%

20%

25%

Ap

r'20

14

May

'201

4

Jun

e'2

014

July

'201

4

Au

g'20

14

Sep

t'20

14

Oct

'201

4

No

v'20

14

Dec

'201

4

Jan

'201

5

Feb

'201

5

Mar

'201

5

Ap

r'20

15

May

'201

5

Jun

e'2

015

July

'201

5

Au

g'20

15

Jan

'201

6

Feb

'201

6

No

v'20

15

Dec

'201

5

Jan

'201

6

Feb

'201

6

Mar

'201

6

Ap

r'20

16

% PS Ball Generation

Graph-1

19

The above graph clearly depicts the lack of PS ball generation by EBI. Further the committee

decided to go to the ground level and find out the reasons which majorly affected the PS Ball

generation.

At Ground Zero the whole process flow was understood i.e. right from the SMS to the SAP & SCP.

The bottlenecks were observed and noted. Cycle time was also noted for the ongoing process to

understand the level of efficiency at which they were performing. Following a couple of visits, an

Action Plan was made entailed the tasks ahead.

Multiple Alternatives were discussed amongst the committee members and data was brought in

from JSPL, Raigarh where the contract is practiced between EBI & JSPL. After Observing the data

inferences were made which depicted a much clearer picture of the costs involved and the reason

for high expenses.

Subsequently meetings were held with the Production Department and the Best Practices Group

Team of JSPL which further discussed the possible solutions and alternatives.

Data Collection

Data Collection played a pivotal role in the completion of this project as it lead to a clearer and

crisper results. The data collection process involved the following:

Approaching EBI and collecting the data of the past 2 years which included Slag

Transported, Slag Atomized & Slag Crushed

Slag produced per year was taken into consideration through which very important

inferences were made

Daily reports were generated and collected (Kress Maintenance, SAP, SCP etc.)

20

Slag Handling costs were collected from different departments and an inference was made

regarding the Net Slag handling cost per ton of steel

Costs of each and every operation were taken into consideration and further analysis was

carried out

JSPL, Raigarh was contacted multiple times for data collection

Kress Maintenance Data was collected

Data from SMS was collected to calculate the cost involved in Slag handling process.

Data Analysis & Discussion

Slag Handling price per ton of Liquid Steel

After reading the contract carefully all the costs were noted and the present scenario was realized

and presented.

Slag handling cost per ton of Liquid Steel depicted a clear picture about the costs that were incurred

by JSPL when lower amount of Slag was Atomized.

1 2 3 (4)=(TS*1) (5)=(TS-4) (6)=(2*3*4*5)/10^7) 9 (8)=(6-7*TS)/10^7 (8*10^7)/SP

PS Ball generation% Slag Crushing Rate(₹) PS Ball Royalty cost(₹) PS Ball Generation(tons) Slag for Crushing(tons) Total Cost Buy back price Final Price Rate per Ton

4% 113 100 1492.4 35817.6 0.4197 225 0.386 30

9% 113 100 3357.9 33952.1 0.4172 225 0.342 26

19% 131 100 7088.9 30221.1 0.4668 225 0.307 24

24% 154 100 8954.4 28355.6 0.5262 225 0.325 25

29% 168 100 10819.9 26490.1 0.5532 225 0.310 24

34% 183 100 12685.4 24624.6 0.5775 225 0.292 22

39% 200 100 14550.9 22759.1 0.6007 225 0.273 21

44% 221 100 16416.4 20893.6 0.6259 225 0.257 20

49% 245 100 18281.9 19028.1 0.6490 225 0.238 18

54% 273 100 20147.4 17162.6 0.6700 225 0.217 17

59% 308 100 22012.9 15297.1 0.6913 225 0.196 15

60% 350 100 22386 14924 0.7462 225 0.243 19

Table-2

21

Table-2 above shows that with increase in Slag Crushing or a decrease in PS Ball generation

increases the slag handling price per ton of steel. At 4% PS Ball generation the rate per ton goes up

to ₹30/- whereas if we look at 60%(As per the contract PS Ball generation should be 60%) the rate

per ton come out to be ₹19/-.

The graph below would further depict how Slag handling price varies with respect to the decrease

in PS Ball generation.

Graph-2 clearly shows the difference in Rate per Ton @60% and @4%(Present rate). The total

costs incurred are also mentioned in this graph which will be discussed later.

The major point to be noted here is that the difference in Rate per ton at different PS Ball generation

rates. If the contract is followed, JSPL could save almost ₹2 crores.

Graph-2

22

Net Impact of Slag Handling Charges per ton of Finished Steel

This calculation was done keeping in mind that all expenses are brought into consideration so that

we could find out the net impact of slag handling on finished steel. The following parameters were

taken into consideration:

Slag Generation

Slag given for PS ball

Slag For Crushing

Electricity charge for Slag Processing(kWh)

Slag Processing Rate

Metal Recovery fee, Metal Recovery

Oxygen Charge

Recovery

Recovery Against PS Ball Production

The purpose of this calculation was to find out:

1. The present net impact of slag handling charges

2. The price of Slag Crushing at which each level of production would incur the same slag

handling charges.

PS Ball Production 0%

Expenses

Particulars Rate Qty Amount

Slag Generation 0.287

Slag given for PS ball 0

Slag For Crushing 113 0.287 32.43

Electricity charge for Slag Processing(kWh) 3 0.287 1

Metal Recovery fee , Metal Recovery @4% 700 0.011 8.04

Oxygen Charge @38 Nm3/ton 7 0.4362 3.05

Slag Handling Expenses Per ton of Steel (in Rs.) = 44.38

Recovery

Oxygen Charge @38 Nm3/ton 7 0.436 3.05

Recovery of Metal @12000/ton (FE min 60%) 12000 0.011 138

Recovery Against PS Ball Production 125 0 0

Total Recovery (in Rs.) = 141

Net Impact of Slag Handling Charges/ ton of Finished steel (in Rs.)

= 96.4

TABLE-3

23

In Table-3 we can see how these factors help us in calculating net impact of slag handling charges

per ton of finished steel. With the current crushing rate, the net impact was affected drastically with

values that changed at every level of production. So the plan was to create an algorithm because of

which now we can keep the costs incurred similar at every stage of production.

24

PS Bal

l Produ

ction

Expens

es

Particu

larsRat

eQty

Am

ount

QtyAm

ount

Rate

QtyAm

ount

Rate

QtyAm

ount

Slag Ge

neratio

n0.28

70.28

70.28

70.28

7

Slag giv

en for P

S ball

00.02

870.05

740.07

175

Slag For

Crushin

g60.6

0.287

17.39

81.20.25

8320.9

7396

106.990

40.22

9624.5

65122

.4564

0.21525

26.3587

5

Electric

ity char

ge for S

lag Pro

cessing

(kWh)

30.28

70.86

0.2583

0.770.22

960.69

0.21525

0.65

Slag Pro

cessing

Rate

60.681.2

Metal R

ecover

y fee , M

etal Re

covery

@4%

7000.01

18.04

0.011

8.040.01

8.040.01

158.04

Oxygen

Charge

@38 N

m3/ton

70.43

623.05

0.4362

3.050.43

623

0.4362

3.05

Slag Han

dling Ex

penses

Per ton

of Stee

l (in Rs.

) =29.3

433

3638.0

9

Recove

ry

Oxygen

Charge

@38 N

m3/ton

70.43

63.05

0.4362

3.050.43

623.05

0.4362

3.05

Recove

ry of M

etal @

12000/

ton (FE

min 60%

)120

000.01

1138

0.011

1380.01

1138

0.0115

138

Recove

ry Again

st PS Ba

ll Produ

ction

1250

00.02

873.59

0.0574

7.180.07

188.97

Total R

ecover

y (in Rs.

) =141

144148

150

Net Imp

act of S

lag Han

dling Ch

arges/ t

on of Fin

ished st

eel (in

Rs.) =

111.5

111.6

111.6

111.7

0%10%

20%25%

TA

BL

E-4

25

Table-4 on the previous page depicts a constant net impact of slag handling charges and the slag

crushing rate was changed to get a constant Net impact at every stage of production.

Major Problems

Apart from the cost analysis, one of the major problems was the inefficiency in the operations

Being carried out by JSPL & EBI. Major problems were:

• No atomizing possible due to unavailability of Kress Carrier; hence the high costs

• Maintenance of Kress Carrier not done by Certified Mechanics which leads to longer and

consecutive breakdowns

• Road No. 8 and the path of the Kress Carrier is not clear; used by other vehicles

Cycle Time Calculation

To get rid of these bottlenecks, the cycle time was calculated for each and every process.

TABLE-5

26

Table 5 shows the cycle time of this complete process.

Kress Maintenance Data

This cycle time was calculated considering the situation at that moment that is with one Kress

Carrier only. Also Breakdown data of both the Kress Carriers was collected and arranged to find

out what were the most common reasons leading to a breakdown.

Table-6 shows the issues that came up in Kress carrier which lead to breakdown and was a major

bottleneck in the process. Using Pivot tables, at any time there was always a Kress Carrier in

breakdown and this affected the process flow of the slag handling process.

TABLE-6

27

During the data collection process it was also found out that on many occasions JSPL themselves

stopped the Atomizing Process for in house usage and all this information was not given to the

concerned team on time.

Summary of the data collection

1. Calculated cost per ton of liquid steel (rate per ton)

2. Calculated Net Impact of Slag Handling Charges per ton of Finished Steel

3. Cycle Time of the Process

4. Kress Carrier Breakdown Data

Figure-4

28

Findings & Suggestions

After taking all the data into account, observations were made and alternatives were suggested to

the concerned team. The following tables depict the alternatives:

Alternatives

ALTERNATIVE-I

• Both the Kress carriers are made available at all times

• This would decrease the losses by almost ₹1.94 crores per year and would also lead to

60% atomizing & 40% crushing as per contract

ALTERNATIVE-II

• Both the Kress carriers are made available at all times as shown in the animation.

TABLE-7

TABLE-8

29

• This would decrease the losses by almost ₹1.94 crores per year and would also lead to

60% atomizing & 40% crushing as per contract.

• But due to decreasing in-house demand of crushed slag, the contract may be negotiated to

increase the PS ball production (to 80%) which would also increase our income. This

would cut our losses by ₹3.82 crores.

ALTERNATIVE-III

No PS balls generation. Only slag crushing done at the rate of ₹113 per ton.

This alternative would lead to piling up of slag and would not generate income.

ALTERNATIVE-IV

TABLE-9

TABLE-10

30

Proposing new slag crushing rates upon negotiation so as to achieve equal cost (per ton of

liquid steel) at each rate.

Also another alternative was considered, which involved ending this contract and starting a new

one with a different firm.

Ecomaister turns out to be the least expensive out of all 3. Also these are 2012(for vista mining

and M/S K.Rao) costs and would have increased in today’s date.The new contracts will include

expenses and would also take considerable time to begin operations.

The following table depicts the scenario.

Slag Qty(tons/year) 5,03,629 5,03,629 5,03,629

Slag Crushing Rate(₹/ton) @ 90-100% 113 220 286

Remarks: Additional

monthly charges

of ₹ 37 lacs

₹14.4 cr

M/S K.Seshagiri Rao & Co.

₹5.69 cr ₹11.07 cr

EcoMaister Vista Mining

Summary of Analysis and Suggestions

Current Status of Ecomaister Operation In Angul

Average generation of PS ball is only 4% of slag generated against 60% forecasted

JSPL incurring higher cost per ton of liquid steel due to lower number of PS ball

generation

Currently we are paying approx. ₹ 30 per ton of ls whereas it can be ₹19 per ton if we

make 60% PS ball (we are considering only slag crushing & PS ball generation costs).

Please refer slide no 3 for details

TABLE-11

31

Why Less Generation of PS Ball?

Kress carrier non availability, frequent break down of Kress carrier

Due to double slag pot operation they are not getting time for making PS ball

A/c of Kress in not working due to which Kress operators are not willing to make PS ball

With single slag pot operation, slag pot is filled 100% with slag & there are chances of

reactions in slag which can spill & can damage the Kress. So we wait to cool down the

slag.

Due to crushed slag requirement in phase 1- b, we stopped PS ball generation for some

time

Most of the time single Kress carrier in operation

Is it possible to make PS Ball in Current Situation?

It is possible to make the PS ball with current single slag pot operation provided Kress carrier is

properly maintained.

32

Conclusions & Recommendation

The following table considers the consequences of continuing and ending the contract with EBI.

Will it be profitable to end it or can we turn the loss into profit?

The following table depicts the pros & cons of the contract with EBI.

TABLE-12

TABLE-13

33

The table below compares the operations with and without EBI. This table critically examines the

scenario.

Personally, I would suggest to continue with the contract but with certain changes:

Amend the crushing rates with respect to a value at which Atomizing is constant.

Change the rates such that at each percentage of PS Ball generation the rate per ton is equal

Maintain both the Kress Carriers at all times. Trained experts should be brought in to

maintain the Carrier.

Road No. 8 (Path on which Kress Carrier moves should be free of vehicles)

In future, EOT can be used to minimize the Kress carrier movement

TABLE-14

34

References

Kress Carrier: Functioning and Models (www.kresscarrier.com)

Data regarding Contract (JSPL, Angul & JSPL, Raigarh and EBI, Angul)

Information about the Organization. http://www.jindalsteelpower.com/

35

Project-II

Forecasting the Production and Price of Steel in India

Steel is an alloy of iron, primarily of carbon and is used in construction and other applications like

construction, machine. They are used majorly because of high tensile strength and low cost. In

India, Iron and Steel Industry in India. At present, India is the largest producer of raw steel and

the largest producer of sponge iron. The industry produced almost 91.46 million tons of total

finished steel and 9.7 million tons of pig iron. Most of the production in India is from Iron Ore.

TATA Iron and Steel Company was established by Dorabji Tata in 1907 and by 1939 it had

launched the largest steel plant in the British Empire. The major companies that produce steel in

India:

TATA Iron and Steel Company

Indian Iron and Steel Company

The Visweswaraya Iron and Steel Ltd.

Bhilai Iron and Steel Plant

Hindustan Steel Ltd. (Rourkela & Durgapur)

Bokaro Steel Ltd.

Salem Steel Plant

Vijayanagar Steel Plant

Vishakhapatnam Steel Plant

Daitari Steel Plant

TATA Steel, Kalinganagar

Dolvi Steel Plant

Jindal Steel and Power Ltd

Bhushan Steel

India is also a major importer of steel although the imports fluctuate. The following table depicts

the trend.

36

Steelmaking Process

Figure-12 clearly illustrates the process of steel making. The basic raw materials used in steel

making are:

Iron Ore

Coal

At JSPL, the major parts of the process were:

Coal Gasification Plant

Direct Reduced Iron (Gas Based)

Steel Melting Shop

Plate Mill / Bar Mill

TABLE-15

Figure-4

37

There are two types of DRI Plants:

Gas Based DRI (JSPL)

Coal Based DRI

In this project the aim was to forecast the price and demand of steel in India.

Methodology

Any forecasting technique has one standard technique to follow:

a) Determine the purpose of Forecast

b) Establish a Time Horizon

c) Select a forecasting technique

d) Gather and Analyze Data

e) Prepare the Forecast

f) Monitor the Forecast

Determine the Purpose of Forecast

The purpose of this forecast is to find out the price and demand of steel in India. It is aimed to

analyze the past, present and future trend of the price and demand of steel.

Establish a Time Horizon

The time horizon established was of 10 years i.e. from January 2005 to December 2015.

Selection of Forecasting Technique

The forecasting technique used is Correlation and Regression Analysis using MS-Excel.

Correlation Analysis: Correlation analysis, analyzes the association between two factors such as

steel WPI and coal WPI in this project. Higher the value the better is the correlation.

38

Regression Analysis: It is a statistical process for estimating the relationship variables. It

establishes a relationship between a dependent and an independent variable. The regression

equation:

Y= a + bX

In regression analysis, the R-Squared value is a measure which depicts how close the data are

fitted to regression line.

Gather and Analyze Data

Different scenarios require different factors. In this project, we chose certain criteria’s which

affect the price and demand of steel. Factors like WPI, production etc. were considered.

Prepare the Forecast

Forecasting is done using the forecasting tools on MS-Excel. Illustrative charts will be prepared

which will demonstrate the trend.

Monitor the Forecast

After all the forecasting has been done, we monitor it to find out if there are any discrepancies.

Data Collection

In any forecasting project, data plays a crucial role. A data would help in understanding the trend

in terms of the following.

Defining

Measuring

Analyzing

Inspecting

Controlling

39

In this study data was collected month wise from January 2006 to December 2015. The data

collection was done from various online and offline sources, details of which have been provided

under the title references at the end of the report.

In this project, there were two aspects of steel that were to be forecasted:

1. Steel Price

2. Steel Demand

Steel Price

For forecasting the price(WPI) of steel we used the following factors:

Coal WPI

Ore WPI

Power WPI

Steel WPI

Exchange Rate ($)

Oil per Barrel Cost ($)

GDP Growth Rate

All these factors were taken into consideration to forecast the price of steel. Table-13 depicts the

data for the year 2006.

Month Coal WPI Ore WPI Power WPI Exchange Rate OIL (/barrel) SteelWPI GDP Growth Rate Oxygen WIP

Jan-06 117.6 139.7 116.1 43.925 60.61 92.7 2.50% 105.1

Feb-06 117.6 133.8 116.9 44.275 58.95 93.7 2.50% 105

Mar-06 117.6 132.4 117.3 44.5 60.01 95.3 2.50% 105

Apr-06 117.6 159 117.6 44.9 67.06 102.6 2.50% 104.2

May-06 117.6 168.6 118.5 46.305 67.33 96.8 2.50% 104.2

Jun-06 117.6 170 121.5 45.88 66.90 95 2.50% 104.1

Jul-06 117.6 171.6 122.5 46.5 71.29 97 1.40% 101.4

Aug-06 117.8 177.2 122.9 46.48 70.87 96.9 1.40% 101.4

Sep-06 117.8 176.3 123.6 45.91 60.94 98.7 1.40% 101.4

Oct-06 117.8 178.3 123.4 44.92 57.26 101.6 3.30% 101.4

Nov-06 117.8 178 122.6 44.6 57.80 100.2 3.30% 101.2

Dec-06 117.8 173.2 120.3 44.115 60.34 99.3 3.30% 101.4

TABLE-16

40

Steel Production

For the forecasting of steel production, we have taken the following factors into consideration:

Coal Production

Iron Ore Consumption

DRI

BFI

Per Capita Consumption

Steel WPI

Steel Production

Industrial Sector Growth

Data Analysis and Discussion

Steel Price

Correlation and Regression Analysis were performed on MS-Excel. The following table depicts

the findings.

Month Coal Production Iron Ore DRI Per Capita Consumption SteelWPI Steel Industrial Sector Growth BFI

Jan-06 38.32 15.18 1.12 0.0037491 92.7 4.05 0.05 2.47

Feb-06 36.9 14.00 1.04 0.0035413 93.7 3.83 0.00 2.26

Mar-06 43.82 16.74 1.22 0.0038974 95.3 4.22 0.03 2.5

Apr-06 31.53 14.572 1.28 0.0037360 102.6 4.05 -0.03 2.19

May-06 33.23 14.741 1.31 0.0037778 96.8 4.10 0.02 2.31

Jun-06 31.92 12.625 1.25 0.0037458 95 4.07 0.00 2.3

Jul-06 30.7 11.149 1.27 0.0038150 97 4.15 0.04 2.27

Aug-06 29.2 10.767 1.22 0.0037463 96.9 4.08 -0.01 2.26

Sep-06 29.2 11.655 1.29 0.0036870 98.7 4.02 0.02 2.25

Oct-06 33.59 13.342 1.39 0.0039026 101.6 4.26 -0.03 2.44

Nov-06 36.4 14.882 1.3 0.0038798 100.2 4.24 0.12 2.4

Dec-06 39.49 17.526 1.35 0.0040033 99.3 4.38 -0.03 2.59

TABLE-17

41

The findings from correlation analysis depict the High Correlation of Steel WPI with:

Coal WPI

Ore WPI

Power WPI

Oil cost per barrel

Exchange Rate

The regression analysis done came out with R square value of 90%. The standard error is

8.98.

Table-16 depicts the regression analysis of the data.

Coal WPI Ore WPI OIL (/barrel) Oxygen WIP SteelWPI Exchange Rate GDP Growth Rate Power WPI

Coal WPI 1

Ore WPI 0.912167 1

OIL (/barrel) 0.477987 0.618205332 1

Oxygen WIP 0.313904 0.21759252 -0.230769345 1

SteelWPI 0.916126 0.911594943 0.650676775 0.191298209 1

Exchange Rate 0.72184 0.654145884 -0.006383516 0.708318552 0.588240789 1

GDP Growth Rate -0.24189 -0.241024359 -0.127596292 -0.049824481 -0.326560474 -0.177815847 1

Power WPI 0.878741 0.883481282 0.464592324 0.492227941 0.848830135 0.848800878 -0.168619866 1

Regression Statistics

Multiple R 0.949227

R Square 0.901032

Adjusted R Square 0.897589

Standard Error 8.997077

Observations 120

ANOVA

df SS MS F Significance F

Regression 4 84750.81658 21187.70415 261.7465586 9.19983E-57

Residual 115 9308.951336 80.94740292

Total 119 94059.76792

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

Intercept 47.02339 7.383412548 6.368787928 4.05826E-09 32.39826945 61.64850796 32.39826945 61.64850796

Coal WPI 0.520472 0.071653545 7.263733399 4.83452E-11 0.378540367 0.662404133 0.378540367 0.662404133

Ore WPI 0.040212 0.015014634 2.678209979 0.008485795 0.010471242 0.069953441 0.010471242 0.069953441

Power WPI 0.372332 0.084142979 4.424993628 2.20425E-05 0.205661098 0.539003192 0.205661098 0.539003192

Exchange Rate -1.20426 0.214326405 -5.618802717 1.36076E-07 -1.628797145 -0.779718427 -1.628797145 -0.779718427

0

50

100

150

200

Ste

elW

PI

TABLE-18

TABLE-19

42

The correlation analysis clearly helped us in figuring out which factor affects the WPI of steel.

This in turn helped in creating a standard equation for regression analysis which was:

= Intercept + Coal WPI*X1 + Ore WPI*X2 + Power WPI*X3 - Exchange Rate*X4

Where X1, X2, X3… are the values in a particular month.

Steel Production

Correlation Analysis

The findings from correlation analysis depict the High Correlation of Steel WPI with:

Coal Production

Iron Ore Consumption

BFI

DRI

Per Capita Consumption

Steel WPI

Regression Analysis

Regression Analysis is done for forecasting the production of steel in India.

The regression analysis done came out with a high R square value of more than 99% and

with an error of 4.29%.

Coal Production Iron Ore BFI DRI Per Capita Consumption SteelWPI Steel

Coal Production 1

Iron Ore 0.002283031 1

BFI 0.534169775 -0.443777514 1

DRI 0.035675631 0.306274336 0.000131629 1

Per Capita Consumption 0.622289042 -0.459039294 0.858798884 0.207549473 1

SteelWPI 0.563059929 -0.396906758 0.737148741 0.198233235 0.870459764 1

Steel 0.623620448 -0.470126798 0.878543526 0.193152845 0.997893463 0.878297942 1

TABLE-20

43

The equation for the regression analysis above is:

Y=-1.1396 + 0.0015 X1 – 0.0054 X2 + 0.1292 X3 + 0.0297 X4 +1265.24 X5 + 0.0014 X6

Trends

Every forecasting project involves analysis of the trend on an annual, monthly or a

quarterly basis. In this project, an yearly trend analysis

Year Month Steel WPI

2006 January 92.7

2006 February 93.7

2006 March 95.3

2006 April 102.6

2006 May 96.8

2006 June 95

2006 July 97

2006 August 96.9

2006 September 98.7

2006 October 101.6

2006 November 100.2

2006 December 99.3

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.999106061

R Square 0.99821292

Adjusted R Square 0.998107798

Standard Error 0.042920619

Observations 109

ANOVA

df SS MS F Significance F

Regression 6 104.9569931 17.49283218 9495.726235 9.9327E-138

Residual 102 0.187902309 0.001842179

Total 108 105.1448954

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

Intercept -1.139630765 0.048677698 -23.4117638 8.11181E-43 -1.236182747 -1.043078782 -1.236182747 -1.043078782

Coal Production 0.001528748 0.000685771 2.229237877 0.027991285 0.000168523 0.002888972 0.000168523 0.002888972

Iron Ore -0.005423609 0.001654337 -3.278417297 0.001428158 -0.008704979 -0.002142238 -0.008704979 -0.002142238

BFI 0.129239564 0.013028938 9.919424312 1.22796E-16 0.103396727 0.1550824 0.103396727 0.1550824

DRI 0.029752951 0.015156437 1.963057051 0.052362718 -0.00030977 0.059815672 -0.00030977 0.059815672

Per Capita Consumption 1265.240636 20.00996738 63.23051968 1.22473E-83 1225.550961 1304.930312 1225.550961 1304.930312

SteelWPI 0.001405903 0.000286964 4.899231641 3.62801E-06 0.000836711 0.001975095 0.000836711 0.001975095

TABLE-21

TABLE-22

44

This graph depicts a trend which could be observed upon careful consideration. E.g. There is a

always an increase in the price of steel always shows an increasing trend in March. It could be

because of the end of financial year and April always has an exponential increase.

GRAPH-3

45

3.7

4.2

4.7

5.2

5.7

6.2

6.7

7.2

7.7

8.2

Stee

l (M

T)

Trend

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Year Steel Produced

2006 4.05

2006 3.83

2006 4.22

2006 4.05

2006 4.1

2006 4.07

2006 4.15

2006 4.08

2006 4.02

2006 4.26

2006 4.24

2006 4.38

GRAPH-4

TABLE-23

46

The trend analysis of production of steel depicts clear increase in the level of production in the

month of March which maybe because of the financial year ending. Also the month of

September shows decline in its production which may be due to the retreating monsoons.

Forecasts Made (Findings)

Steel Price

Steel Price was forecasted with very minute variance. In the excel sheet prepared, we can put the

values and forecast the price of steel in that particular month. Also we can forecast the WPI of

coal, ore etc. using moving averages method.

Steel Production

Similarly, production of steel was also forecasted and color formatting of the cells was done to

find out when the variance was more than the standard error.

Month Coal WPI Iron Ore WPI Power WPI Exchange Rate$ Steel WPI Real WPI Variance

Nov-15 189.8 340.1 177.9 66.462 145.68 139.9 -0.0413

Dec-15 189.8 306.8 176.8 66.208 144.24 137 -0.0528

Month Coal(MT) Iron Ore(MT) BF(MT) DRI(MT) Per Capita Consumption(/MT) Steel WPI Steel(MT) Real Production Variance

Dec-15 58.37 11.52433 4.78 1.71 0.005724 162.20 7.0241 7.07 0.006496

Jan-16 62.9 11.55000 4.76 1.51 0.005605 144.8 6.8468 7.41 0.076009

Feb-16 60.1 11.60650 4.78 1.50 0.005590 139.90 6.8182 6.94 0.01755

TABLE-24

TABLE-25

47

Conclusion

The aim of this project is to forecast the Price and Production of Steel in India. Using Correlation

and Regression Analysis, forecasting was done and a model was created for Forecasting the Price

as well as the Production.

Also a trend analysis was done in this project to understand the kinds of trend the price and

production of steel follow.

A model was created which upon entry of values will predict the production and the price of the

steel in the subsequent month.

48

References

Monthly Steel Prices and Production. (2013-2015). Steel 360, Steel Mint & Iron & Steel

Review

Kutner, M.H., Nachtsheim, C.J., Neter, J., Li, W. (2004). Applied Linear Statistical Models.

Monthly Production of Steel. Retrieved from: https://www.worldsteel.org/media-

centre/press-releases.html

Monthly WPI of Coal, Ore and Steel. Retrieved from: http://www.indiastat.com/default.aspx

Monthly Production of Steel. Retrieved from: http://www.steelmint.com/

Statistical Review of World Energy. Retrieved from:

https://www.bp.com/content/dam/bp/pdf/energy-economics/statistical-review-2015/bp-

statistical-review-of-world-energy-2015-full-report.pdf

Industrial Sector Growth in India. Retrieved from: http://www.oecd.org/india/

Information about Indian Steel Sector. Retrieved from: http://steel.gov.in/

Information about Coal Production. Retrieved from: http://coalindia.in