II Rudarsko Geološki forum, Prijedor 2016

7/25/2019 II Rudarsko Geoloki forum, Prijedor 2016

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2016

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Marcela Gotelip Barbosa, G. Siboni, F.Guimaraes Vasconcelos, Armando Correa de

Araujo,Tim Sylow, Marie-Jeanne Venturini

OVERVIEW OF ARCELORMITTAL MINING OPERATIONS AND RESEARCH &

DEVELOPMENT FUNCTION .......................................................................................................... 1

Marcela Gotelip Barbosa, G. Siboni, F.Guimaraes Vasconcelos, Armando Correa de

Araujo,Tim Sylow, Marie-Jeanne Venturini

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100 ""


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OVERVIEW OF ARCELORMITTAL MINING OPERATIONS AND

RESEARCH & DEVELOPMENT FUNCTION

Marcela Gotelip Barbosa1, G. Siboni1, F. Guimares Vasconcelos1, Armando Corra de

Araujo1, Tim Sylow1, Marie-Jeanne Venturini2

1ArcelorMittal Maizires Mining and Mineral Processing Research Center2ArcelorMittal Maizires Process Research Center

1. INTRODUCTION

ArcelorMittal is among the largest worlds producers of iron ore. With a geographically-

diversified portfolio of iron ore and coal assets, it is strategically positioned to serve the

network of steel plants, as well as supply the external global market. While ArcelorMittal

steel operations are important customers, the supply to the external market is constantly

increasing. ArcelorMittal Mining has a global portfolio of 14 operating units with mines in

operation and development. In 2015, the mines and strategic contracts produced 73.7 million

tons of iron ore and met 62% of the companys iron ore requirements. The company also

produced 6.29 million tons of coking coal and PCI (Pulverized Coal injection), meeting 15%

of the companys PCI and coal requirements.

Innovative thinking is encouraged across ArcelorMittal thanks to the influence of

ArcelorMittals research and development team. Research and development (R&D) helps thecompany to realize its ambitions in technological innovation, to support its sustainability

goals as well as ensuring future growth. With 1,300 full-time researchers in 11 research

centers across the globe, ArcelorMittal R&D is highly business oriented, ensuring a shorter

time to market and improved competitiveness in a variety of sectors, including Mining.

1. IRON ORE MINES

ArcelorMittal Mining currently has iron ore mining activities in Brazil, Bosnia, Canada,

Kazakhstan, Liberia, Mexico, Ukraine and the United States. Iron ore products include

concentrate for sintering and pelletising, pellets, and direct shipped fines and lump ore.. As ofDecember 31st2015, ArcelorMittals iron ore reserves are estimated at 4.3 billion tons run of

mine. The figure 1 is presenting the worlds map including the location of each iron ore mine.

a. ArcelorMittal Mining Canada (AMMC)

Located in Mont Wright, Quebec, AMMC is the largest iron ore producer among

ArcelorMittals mines. In 2015, the company produced 25.8 million tons of sinter feed

concentrate and pellets. The deposit is a banded iron formation with hematite as the only iron-

bearing mineral. The mine is an open-pit operation producing Run of Mine ore at

approximately 30% Fe. Beneficiation of the ore is achieved through crushing, screening,

grinding, classification and gravity separation. The resultant product is a coarse concentrate


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sold as sinter feed to the market. Prior to pelletizing, the ore is further classified and

concentrated by spirals at Port-Cartier. Sinter feed concentrate accounts for approximately

60% of total sales from AMMC.

Figure 1: World map showing the location of ArcelorMittal iron ore mines

b. Baffinland Iron Mines (BIM)

BIM is a 50:50 joint venture between ArcelorMittal Mining and Nunavut Iron Ores Holdings

LP, with ArcelorMittal Mining as operator. The main asset is the Mary River mine, an opencut operation, which commenced mining in late 2014.The mine is located in the north central

plateau of Baffin Island, approximately 160 km directly south of the settlement of

Mittimatalik (Pond Inlet) in the north of Canada, in the province of Nunavut well inside the

Arctic Circle. It is a high-grade hematite body in majority, with portions of magnetite and few

goethite encompassing also iron silicates and quartz as the gangue material. The process was

design to maximize the production of Lump Ore, with a crushing system followed by

screening. Today the production is divided in 70% of lump production and 30% of fines, with

an estimated total production of 6.5 Mtpa in the final stage of the project. One particularity of

Baffinland is that due the hard weather conditions in the polar circle, shipping is restricted to

the summer season, when all the production has to be shipped inside a 70 to 80 day window.

c. Minorca and Hibbing Mines

Minorcamine produces about 2.7 million tons of fluxed iron-bearing pellets and Hibbing

Taconite Mines produces about 5.1 million tons of pellets (data from 2015). Taconite, banded

iron formation composed mainly by magnetite and quartz, is mined in both mines and

processed by crushing, grinding, classification and magnetic concentration. In Minorca,

reverse flotation of quartz is also applied to further concentrate the ore. The final concentrate

from both mines are agglomerated in the pellet plants and sold in the US market.


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d.

ArcelorMittal Mexican Mines

Pea Coloradamine is located in the north of the Sierra Madre del Sur, in the north-west part

of the state of Colima, Mexico. This operation is a 50/50 joint-venture between ArcelorMittal

and Ternium S.A. The ore is composed mainly by magnetite, approximately 89% of itscomposition, and of different phases of gangue particles, including silicates. The ore is

processed by crushing, grinding, classification and magnetic concentration to produce, in

2015, 1.7 million tons of pellet-feed as ArcelorMittal production share. All pellet feed is

transformed into pellets.

Volcan/Sonora mine is located in the north of Mexico, near the cities of Obregon and

Guaymas in the state of Sonora. The ore is composed by iron oxides, as magnetite, iron

sulfides, as pyrite and the presence of apatites, as fluorapatite and chlorapatite. Other gangue

minerals are also encountered as quartz, calcite and grunerite. The crushing facilities at the

mine include crushing, a dry cobbing magnetic separator and four tertiary crushers. The ore isthen transported by truck to the concentration plant,

which is located 120 kilometers from the

El Volcan mine facility, and it includes two ball mills on line, a magnetic separation circuit,

flotation systems (sulfide and phosphate removal), a belt conveyor filter and a disposal area

for tails.The annual production in 2015 was 1.7 million tons of concentrate and pellets.

Las Truchasmine is located near the steel plant at the port of Lzaro Crdenas, south-east of

Mexico. Las Truchas mine is an integrated iron ore operation that includes mine exploitation,

crushing, dry cobbing pre-concentrate and final concentration performed by magnetic

separation. Mineralogical analysis of the ore show a presence of some sulfides

(pyrite/pyrrhotite) and the main iron-bearing phases are magnetite and hematite with someparticipation of goethite.The annual production of Las Truchas mine in 2015 was 1.8 million

tons of iron ore concentrate, lump and fines. All the three mines in Mexico supply iron ore to

the steelmaking facility located at Lzaro Crdenas, also in Mexico.

e. ArcelorMittal Brazilian Mines

Serra Azulmine lies within the iron quadrangle, in Itatiaiauu, which is located 70 km south-

west ward from Belo Horizonte, Minas Gerais State. The current operation consists of mining

and processing the friable itabirite (Banded Iron Formation), which produce lump and sinter

feed being sold on both domestic and international markets. Serra Azul ore is mainly

hematitic and main gangue phase is quartz. The beneficiation plant consists of crushing,classification, gravity (jigging and spiral concentration) and magnetic separation (wet rare

earth drums and WHIMS). The annual production of Serra Azul mine in 2015 was 1.5 million

tons of lumps and fines.

Andradeis an open pit mine situated in the south-east of Brazil, in the state of Minas Gerais.

The deposit is located in the Iron Ore Quadrangle and it is classified by Banded Iron

Formation. Principal minerals are hematite and quartz. The processing plant is composed only

by crushing and screening, no concentration is applied since only hematite body is exploited.

The sinter-feed produced is transported by railway to Joo Monlevade steelmaking plant,

which is around 8 km away. The annual production in 2015 was 1.5 million tons of fines.


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f.

ArcelorMittal Prijedor

Buvaopen-pit mine is situated near the town of Prijedor in the north-west of Bosnia and

Herzegovina. Its a Bilbao type deposit in Upper-Carboniferous to Lower Triassic limestone.

Principal minerals are goethite and siderite. The ore contains around 43% Fe and reserves areestimated at 180 Mt of ore. The goethite ore is processed in the GMS beneficiation plant to

remove mainly silica where crushing, scrubbing, classification and magnetic separation by

WHIMS and SLon are applied. The product is filtered by vacuum and press filtration before

being transported by railway to Zenica steelmaking plant. The annual production in 2015 was

2.1 million tons of lumps and fines.

g. ArcelorMittal Ukrainian Mines

ArcelorMittal Kryvyi Rih is the largest full-cycle metallurgical enterprise of the Mining and

Metallurgical Complex of Ukraine.

The open-pit mine in Kryvyi Rih is producing magnetite iron ore concentrate with Fe ~65%

from the mined crude ore at Fe ~34%. The processing plant has a capacity of approximate 25

million tons of crude ore per year and 10.1 million tons of concentrate per year (data from

2015). The beneficiation process includes crushing, grinding, classification and a series of

magnetic separator units to upgrade the ore and ultimately achieve a high iron grade (>65%)

magnetic concentrate.

The Ukrainian Underground mine is called Artyomand it is basically a hematitic ore, with

approximately 48-52% Fe content and 14-18% SiO2 content. The process flowsheet ofArtyom mine comprises only crushing and screening facilities to produce 0.9 million tons of

lumps and sinter feed (data from 2015).

h.

ArcelorMittal Kazakhstan Mines

ORKEN is the name of ArcelorMittal Iron ore department in Kazakhstan which manages the

four local ArcelorMittal mines. The total production of the mines is transported to

ArcelorMittal Temirtau steelmaking facility, also in Kazakhstan.

The Lisakovskymine is a sediment marine iron ore with goethite free or almost free oolithes.

The annual production is around 0.9 million tons of concentrate (data from 2015). The ore is

beneficiated by jigs, classifiers, and wet high intensity magnetic separators to yield a gravity-

magnetic concentrate, upgrading the ore from 39.8%Fe to 49%Fe. The phosphorus content is

quite high, varying from 0.6% to 0.8%P.

The Atasumine is located near the town of Karajan in the Atasu district. The mine deposit is

a skarn. The ore is composed by 25% Hematite and 75% Magnetite. At the beginning of its

operation in 1954, the mine was an open pit but until the 70s it was changed to underground

mine with a production of 0.9 million tons of lumps and fines per year in 2015. The

beneficiation of the ore is done by crushing, screening and gravity separation by jigging.


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The Kentobemine is an open pit mine with a capacity of 1.5 to 2Mt/y but the production was

only 0.9 million tons in 2015. The mine deposit is a skarn with massive magnetite ore. This

iron ore contains an important amount of sulfides. The process flowsheet comprises three

stages of crushing, classification and magnetic separators is applied to remove gangue

minerals but the concentrate remains with high level of sulfur content (>2-3 %).

Atansor open-pit mine is located in north-central Kazakhstan, about 45 km north-west of

Stepnogorsk. The deposit is a moderately dipping skarn magnetite of magmatic origin, but the

ore has been oxidized and enriched due to weathering in some zones. The main result of

weathering is martite, with hematite and goethite also present. The mine produces hematitic

(martite) lump and fines and the beneficiation plant comprises crushing, screening and

magnetic separation. The annual production in 2015 was 0.4 million tons.

i. ArcelorMittal Liberia

ArcelorMittal Liberian deposits all belong to the Nimba mountain range, in the north-east of

Liberia. All ArcelorMittal Liberian deposits have approximately the same geological

configuration: first itabirites, a metamorphosed Banded Iron Formation (BIF) then a

weathering profile composed of a transitional zone and finally a laterite horizon, or canga.

Deposits are composed of three iron oxides: magnetite, hematite and goethite and quartz as

the main (and sometimes the only one) gangue mineral. ArcelorMittal actually possesses 3

concessions in the Nimba region: the Tokadeh, Gangra and Yuelliton deposits. The Tokadeh

is nowadays producing a Direct Shipping Ore (DSO) product and exploitation of the

transition zone should begin in a near future. The DSO is processed only by dry crushing andscreening to produce 4.3 million tons of sinter-feed (data from 2015).

2. Research and Development activities

a. Mining and Mineral Processing

The ArcelorMittal group is actively developing its raw material base to raise self-sufficiency

levels, and for this reason, the research Centre of Mining and Mineral Processing (MMP) was

created in 2008 within ArcelorMittals Global Research & Development in Maizires-ls-

Metz, France. Since its establishment, MMP has been developing processing solutions forboth existing operations and new projects, with iron ores from Europe, Asia, America and

Africa. The main missions of MMP are to contribute to ArcelorMittals overall strategy to

increase iron ore self-sufficiency, to provide technical assistance to existing mineral

processing plants improving efficiency, increasing safety, decreasing environmental impacts

and operation costs, to develop conceptual level studies for the beneficiation of new potential

sources of iron ores, to characterize raw material sources for iron making and to identify and

assess emerging trends in the field of iron ore characterization and processing. In addition,

MMP supports sales and raw material purchasing activities. In terms of expertise, MMP

performs:


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Mineralogical characterization and interpretation

Design, supervision and conduction of mineral processing test-work programs

Process flowsheet design and simulation

Equipment sizing and selection (pre-scoping/scoping level) Plant audits and identification of potentials for optimization

Benchmarking of mineral processing unit operations.

As example of the latest achievements of MMP team, it is possible to mention the

development of new sinter-feed fines products from Liberia and the development and

subsequent marketing and sale of Baffinland lump at a premium price in the pellet market. In

addition to that, the design for reconfiguration of the crushing circuits at Baffinland enabling a

50% improvement in throughput. Other examples are the improvements achieved on the low

grade ore concentration flowsheets for Bosnia and Pea Colorada (Mexico), these

achievements being very important to supporting sustainable ongoing operations at thesemines. At last, but not least, the work performed for tailings thickening in the Ukrainian

operation which has the potential to reduce energy costs in the Ukraine by several million

dollars per year.

b. Research activities for AM Prijedor and AM Zenica

Since 2009, MMP has been contributing to technological improvements in the GMS

beneficiation plant of ArcelorMittal Prijedor.

Since the exploitation in Jezero Pit in Omarska

Mine was over some years ago, ArcelorMittal Prijedor started to exploit the Buva Mine. The

two deposits are near to each other but they have different mineralogical characteristics and itaffects a lot the mineral processing of the ore. Fe content in Buvac Pit is lower by

approximately 4% against Jezero Pit. Therefore, the studies were focusing on plant

optimization in order to improve the beneficiation of this new ore trying to keep as much as

possible the design of the plant. Laboratory and pilot scale tests were performed throughout

the years, the feasibility of the project was evaluated and finally in 2014, two magnetic

separators (SLon) to treat the -1+0.5mm ore fraction and one filter-press, to recover the -

0.025mm fraction, were installed at GMS plant adding value to the process. Research and

development activities are still going on especially for the quality improvement of the -

0.025mm fraction and possible recovery of Fe rich tailings pond material.c. Sinter pot tests with Prijedor ores for Zenica sinter plant

ArcelorMittal Maizires Process Research Center, located in the same site as MMP, is

equipped with a sinter pot pilot to simulate the sintering process and access results as

productivity, sinter quality and energy consumption. This tool allows to characterize various

ores mixes and fluxed and to define optimal sintering operational conditions.

In 2009, first study is done in a context where the sinter strand at Zenica was bottleneck in

terms of hot metal production so the increase of sinter productivity was considered as first


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priority. Different possibilities were studied to attain this objective and sinter pot test was

performed to optimize the sinter mix with a maximum of local iron ore. Significant increase

of productivity was obtained replacing the initial ore mix with 80% of Bosnian sinter-feed ore

and 20% of Kryvyi Rih concentrate, with very fine size distribution, by 100% of Bosnian

sinter-feed ore with addition of 1% burnt lime in mix and optimization of the moisture leading

to improvement of granulation process. However, the solid fuel consumptions were increased

with the increase of Bosnian BPR goethite ore.

Recently, another series of trials were performed in the sinter-pot aiming to characterize the

sintering performances of Buva (BPR and BPR+) and carbonate ores. The objective of the

trials is to assess the possibility of using binary mixes: BPR or BPR+ with carbonate ore

without negative impact on sintering conditions and sinter quality. The usual Buva ore used

in Zenica sintering plant is called BPR and it contains around 10% of -0.025mm. With the

new configuration of the GMS plant, filtration residue of very fine ore in form of dense cake,from press filter, is available and can be used in the sinter plant. 7 to 10% of this very fine

compound is added to BPR to constitute BPR+. The sinter pot tests show a light but

acceptable decrease of productivity (-1t/m2/d) with BPR+ compared to BPR.

Other ore named Carbonate ore (~26%Fe, ~14% CaO, ~2.4% SiO2, ~4.8% MgO ) is also

available in Ljubija deposit close to the current mine. This ore very poor in Fe but with high

amount of CaO and MgO could replace a part of fluxes such dolomite and a part of limestone

in the sinter blend while allowing increasing the level of iron in sinter. Results were

encouraging and showed that carbonate ore can be used in the sinter plant replacing fluxes in

the order of maximum 30% in the sinter mix without decrease of productivity, with increaseof Fe content in sinter (+1.8%) but also increase of MgO content in sinter to 2.2%. This level

is high but not detrimental in Zenica conditions. Sinter quality is slightly worse compared to

when only BPR and fluxes are used.

These encouraging results have to be confirmed during industrial trials in Zenica sinter plant

at end of 2016.


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ARCELORMITTAL-A

Marcela Gotelip Barbosa1, G. Siboni1, F. G. Vasconcelos1, A. Corra de Araujo1,

T. Sylow1, M.J.Venturini2

1ArcelorMittal Maizires Mining and Mineral Processing Research Center2ArcelorMittal Maizires Process Research Center

1.

ArcelorMittal . , , . ArcelorMittal-a , . ArcelorMittal Mining 14 . 2015. , 73.7 , 62% . , , 6.29 PCI (eng Pulverized Coal injection), 15% PCI.

ArcelorMittal-u, ArcelorMittal-a . (R&D) ,, . 1300 11 , ArcelorMittal R&D , , Mining.

2.

ArcelorMittal Mining , , ,, , -. , ,

. 31. 2015. , ArcelorMittal-a 4.3 . 1. .

2.1. ArcelorMittal Mining Canada (AMMC)

Mont Wright-u, Quebec, AMMC ArcelorMittal-u. 2015., 25.8 . . , 30% Fe. , , , . , .


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, Port-Cartier-u. 60% AMMC-a.

1: ArcelorMittal-a

2.2.Baffinland (BIM)

BIM 50%:50% ArcelorMittalMining-a Nunavut Iron Ores Holdings LP. Mary River ,2014. . Baffin, 160 km Mittimatalik (PondInlet), , Nunavut - ., , . , , . 70% 30% , 6.5 . Baffinland-a ,

, , 70 80 .

2.3. Minorca Hibbing

Minorca 2.7 , Hibbing 5.1 ( 2015). , , , , . Minorca, .

-.


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2.4. ArcelorMittal

Pea Colorada Sierra Madre del Sur, - Colima, . 50%:50%

ArcelorMittal-a Ternium S.A. , 89%, , . , , , 2015. , 1.7 ArcelorMittal-ov . .

Volcan/Sonora , Obregon y Sonora. , ,, , . , . , cobbing

. , 120 El Volcan, , , ( ), . 2015. 1.7 .

Las Truchas Lzaro Crdenas, - . Las Truchas , , cobbing - .

(/) , . LasTruchas 2015. 1.8 . LzaroCrdenas, .

2.5. ArcelorMittal

Serra Azul (iron ore quadrangle), Itatiaiauu, 70 km - Belo Horizonte, MinasGerais.

(), . Serra Azul . , , ( ) (WHIMS). Serra Azul 1.5 .

Andrade -, Minas Gerais. . .

,


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. Joo Monlevade, 8 km.2015. 1.5 .

2.6. ArcelorMittal

-. bilbao - -. . 43% Fe 180 mil.t . - ,, WHIMS i SLon . ,, , 2015. 2.1 .

2.7. ArcelorMittal

ArcelorMittal Kryvyi Rih .

Kryvyi Rih Fe~65% Fe ~34%. 25 10.1 ( 2015. ). , ,, (>65%) .

Artyom , 48-52% Fe 14-18% SiO2 . Artyom 0.9(2015. ).

2.8. ArcelorMittal

ORKEN ArcelorMittal-ovog ArcelorMittal-ova . ArcelorMittal Temirtau, .

Lisakovsky . 0.9 ( 2015.). , , -, 39.8% Fe 49% Fe. , 0.6% 0.8% P.

Atasu Karajan, Atasu. . 25% 75% . 1954. , 70- 0.9 2015. .


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, .

Kentobe 1.5 2 mil. t/god

0.9 2015. . . . , , , , (>2-3 %).

Atanasor , 45 km -Stepnogorsk-a. , . , . ()

, . 2015. 0.4 .

2.9. ArcelorMittal

ArcelorMittal Nimba , - . ArcelorMittal-ova : , (BIF), , , , canga . :, , ()

. ArcelorMittal, , 3 Nimba : Tokadeh,Gangra i Yuelliton . Tokadeh (DSO) .DSO 4.3.(2015. ).

3.

3.1.

ArcelorMittal

, 2008. (MMP), ArcelorMittal-ov Maizieres-les Metz, . MMP -, , , , . MMP-a ArcelorMittala , , , , , , . MMP :


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. . , .

, (, +) . : +, , . 10% -0.025 mm. (-) 7 10%-, +. , ,, (-1 t/m2/d).

, (~26% Fe, ~14% CaO, ~2.4% SiO2, ~ 4.8% MgO). , CaO i MgO. ( ), .30%, , Fe (+1.8%), MgO 2.2%. , . , .

, 2016.


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METALOGENETSKAKARTA

LJUBIJSKEOBLASTI

RUDARSKIINSTITUTD.O.O.PRIJEDOR

,2015.god.

Autori:

Prof.drAleksandarGrubi,akadem

ik

Prof.drRankoCviji,dipl.in.geologije

DrAleksejMiloevi,dipl.in.geologije

Miodragelebi,dipl.in.rudarstva

0

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LEGENDA: G

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rijetkimpojavama

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ta

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. . (2016) , :

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1:50.000 . .

[1] , . , . 1991. . -, . ArcelorMittala, .


30/480

II - , 2016

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

Garai, V. i Jurkovi, I. 2012. Geochemical characteristic of different iron ore types from theSouthern Tomaica deposit, Ljubija, NW Bosnia. Geologia Croatica, vol. 65, No. 2, str. 255-270. Zagreb., . , . 2003.

. : , . 63- 137. . ., ., , . , . 2006. . II , .32-34. . .., ., ., ., 2016. . ., . 1988. . - .., . 1971. . , . XI. . 1-146. ., . 1973. - .

. ,.Strmi-Palinka, S., Spangenberg, J. E. i Palinka, A. L. 2009. Organic and inorganicgeochemistry of Ljubija siderite deposits, NW Bosnia and Herzegovina. Min. Deposita, vol. 44,

No. 8, str. 893-913. Springer Verlag., . 1981. . -, . 1-135. . ., ., ., 1980. 1981-1985. , . 8, "" , . 7-14.


31/480

II - , 2016

M. 1, .

1, .1, .

1

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.

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.

OVERVIEW OF MATHEMATICAL MODELS FOR PIT

OPTIMIZATION AND PLANNING

Abstract: Contemporary mining has constant declining trend in business conditions. Achievement

possibilities of economic and other goals of mining projects are being compromised by constant

deposit deterioration where exploitation is being held, as well as a significant dose of uncertainty

associated with geological, economic and technical parameters of production. In such complexbusiness conditions, mathematical models, able to respond on significant challenges, i.e. to offer

optimal solutions which shall guarantee maximal fulfillment of projected goals, are considered to be

necessity.

Current approach to optimization and planning of mines, can be divided into two categories conventional

(deterministic) and stochastic. Their main characteristics of conventional methods are based on

deterministic approach during adoption of relevant input parameters. In last two decades, adoption of

stochastic models is considered to be serious alternative. Numerous results of scientific work strongly

suggest that stochastic mathematical models significantly better describe the nature of contemporary

mining, and represent alternative capable of offering better solutions.


32/480

II - , 2016

This paper gives an overview of the basic conventional and stochastic algorithms for optimization and

planning of open pit, with a critical focus on the advantages and disadvantages of both approaches.

Keywords:optimization, mine planning, mathematical models, deterministic and stochastic approach.

1.

, , [1]. . , , . , , . , 1.

1.

., , , , , . ,

:


33/480

II - , 2016

.

, . , [2,3].

,-. , ()[4-8].

,, .

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[9,10]

.

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.

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. , - .

, .

,

. 1.

1.

(

)

[11]Lerch Grossmann 2D

[13]

Lerch Grossmann 3D

[14, 15]

[12] 3[14] , [16]


34/480

II - , 2016

. , . , . , () . . , () .

, Lerch Grossmann 2D . .. , .

Lerch Grossmann 3 . . . : (. arcs) . Lerch Grossmann 3D () , 3D .

, . , 2.

2.

Johson

[17]

Gershon

[18][20]

/,

[19]

Dowd Anur

[21]

() (1969) . , . .


35/480

II - , 2016

.

() .

[20] . .

Dowd Anur [21] . .

. .

2.1.

, . , , .

. [22,23].

.

.

3.

, , . .

, . .


36/480

II - , 2016

.

, . . Goovaerts (1997) , , (. smoothingeffect) . Ravenscroft [24] . . , , , .

, Godoy Dimitrakopoulos [25] (.Simulated annealing) .

Ramazan Dimitrakopulos [26] . . , .

-, . , , . , . , , .

( ) . , , ()

[27].


37/480

II - , 2016

3.1.

,

, .

, , .

4.

. , .

() , .

. , . , ().

, . . , . .

, , () .

:

[1] Erdem, ., Gyagler T., and Demirel, N., Uncertainty assessment for the evaluation of netpresent value: a mining industry perspective, The Journal of The Southern African Institute ofMining and Metallurgy, 2012, Volume 112, str. 405 - 412

[2] Ramazan S, Open pit mine scheduling based on fundamental tree algorithm, doktorska disertacija,2001, Colorado School of Mines.

[3] Darwen, J, P, Genetic Algorithms and Risk Assessment to Maximise NPV With Robust Open-PitScheduling, Strategic Mine Planning Conference, 2001, Perth

[4] Dowd, P, A, Pardo-Igzquiza, E, The Incorporation of Model Uncertainty in GeostatisticalSimulation, Geographical and Environmental Modelling, 2002, Vol.6, str. 147-169.

[5] Benndorf, J. Dimitrakopoulos, R., New efficient methods for conditional simulation of large

orebodies. Orebody Modelling and Strategic Mine Planning, The Australasian Institute of Mining,2007.


38/480

II - , 2016

[6] Dimitrakopoulos, R, Conditional simulation algorithms for modeling orebody uncertainty inopen-pit optimization. International Journal of Surface Mining Reclamation and Environment,1998, Vol. 2, No. 4, str. 173-179.

[7] Dimitrakopoulos R, Farrelly C, Godoy M, Moving forward from traditional optimization: Grade

uncertainty and risk effects in open pit design, Mining Technology, 2002, Vol. 111, str. 82-87.[8] Dimitrakopoulos R., Ramazan S, Uncertainty based production scheduling in open pit mining,

SME Transactions, 2004, vol. 316.[9] Pitkanen, P, Open Pit Optimization, Calculating the Optimum Pit Limits, Helsinki University of

Technology, Laboratory of Rock Engineering, 1997, ISBN 951-22-3877-2.[10]Osanloo, M, Gholamnejad J, i Karimi, B, Long-term open pit mine production planning: a review

of models and algorithms, International Journal of Mining, Reclamation and Environment, 2008,Vol. 22, No. 1, str. 3-35

[11]Pana, M. T, Carlson, T.R, A Description of Computer Technique Used in Mine Planning of theUtah Mine of Kennecott Copper Corp, VI APCOM, 1966, State College, Pennsylvania

[12]Philips, P, A, Optimum Design of Open Pit, X-ti APCOM, Johanesburg, South Africa, 1973.[13]Lerchs, H and Grossmann, Optimum design of open pit mines, Transactions CIM Bullitin, 1965,

vol. 58, str. 17-24.[14]Johnson, T, B, i Sharp, W, R, A ThreeDimensional Dynamic Programming, Method for Optimal

Open Pit Design, Bureau of Mines, 1971, U.S. Dep. of the Interior[15]Zhao, Y, Kim, Y, C, A new Optimum Pit Design Algorithm, XXIII-ti APCOM, 1992, str. 423-

434[16]Davis, R, E, Williams, C, E, Optimisation Procedures for Open Pit Mine Scheduling, XI-ti

APCOM, University of Arizona, Tucson, Arizona, 1973, Vol. 1C, str. 1-18[17]Johnson, T.B., Optimum production scheduling, Proceedings of the 8th International Symposium

on Computers and Operations Research, 1969, str. 539 562.[18]Gershon, M.E., Optimal mine production scheduling: evaluation of large scale mathematical

programming approaches. International Journal of Mining Engenering, , 1983, vol. 1, str. 315-329[19]Dowd P.A., & Onur A.H., Optimization of Open-pit Mine Design-Part 1: Optimal Open-pit

Design, Transactions of the Institute of Mining and Metallurgy, (Section A, Mining Industry), vol.102, 1993, str. A95-A104

[20]Dimitrakopoulos R., Strategic mine planning under uncertainty, stochastic optimization forstrategic mine planning: a decade of developments, Journal of Mining Science, 2011, Vol. 47, str.138-150

[21]Dimitrakopoulos R., Griffin W.H, Geology-based Conditional Simulation in the Athabasca OilSands Deposit, Alberta, Canada, Natural Resources Research, 1993, Volume 2, str. 49-61

[22]Dimitrakopoulos R, Ramazan S, Stochastic integer programming for optimizing long termproduction schedules of open pit mines: methods, application and value of stochastic solutions,Mining Technology, Transactions of the Institute of Mining and Metallurgy, Section A, 2008,Vol. 117, No. 4, str. 155-167.

[23]Erdem, ., Gyagler T., and Demirel, N., Uncertainty assessment for the evaluation of netpresent value: a mining industry perspective, The Journal of The Southern African Institute ofMining and Metallurgy, 2012, Volume 112, str. 405 - 412

[24]Ravenscroft, P, J, Risk analysis for mine scheduling by conditional simulation, Transactions ofthe Institute of Mining and Metallurgy, (Section A, Mining Industry), 1992, Vol. 101, str. 104-108.

[25]Godoy M. C., Dimitrakopoulos R., Managing risk and waste mining in long-term productionscheduling, SME Transactions, 2004.

[26]Ramazan, S, Dimitrakopoulos, R, Production scheduling with uncertain supply: A new solutionto the open pit mining problem, COSMO Stochastic Mine Planning Laboratory, Technical Report,2007, str. 257-294.

[27]StevanoviD, Kolonja, B, Stankovi, R, Kneevi, D, Bankovi, M, Application of stochastic

models for mine planning and coal quality control, Thermal Science, 2014, vol. 18, str. 1361-1372


39/480


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II - , 2016

, , ArcelorMittal Maizieres ArcelorMittal .

, , :

.

, - 30 7t/h. , .

2.

() , . (30% -0.0025mm) , . 20% Fe 60% Fe.

: , .

3.

, cutoff 35% Fe. Na ovaj nain je prosjeni sadraj u ulaznoj rudi bio 48%Fe.

cutoff 32% Fe, . 46.5% Fe. 10%.

3.1. -

:

(-8+0 mm) (-40+8 mm), i () .

70% Fe 80%.

20% 80%.


41/480

II - , 2016

, , 1.

1. -

, (+0-150 mm) , . :

(1 1.), GISL-72

30 20 mm (2), -150+30 mm 40 mm (3), GISL-62 1.6 mm (4), GISL-62 20 1.6 mm (5), (Barmac ) -20 +1.6 mm (19)

- (I),

-5 +0 mm (6), ( -3 +0 mm)

250 mm (7) (10b),

I

III

II

IV


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II - , 2016

Jones DP-317 (9), (8) a (11) (12), 30m (IV),

Slon 2500(15, 18) (16) (14, 17), - (II),

(10a) Bilfinger GHT - 2000 (20) (III).

, , -.

. , - .

.

3.2. -

3.2.1.

-2009. - , .

() () , . 45%:55%10%:90%, .

-, BARMAC B7150SE

VSI, 2 x 150 t/h, RF SH 3000 x 7300 DD-2 , UR 915/1500-VA-Sond, VT 40 05 HC, 3KW. 2. .


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II - , 2016

2.

(1 2) , , .

1.

AsortimanMasa namokro,

mil t

Masa nasuvo,

mil t

Fe% Mn% SiO2% H2O%Iskoritenje

mase na

mokro,%

Iskoritenjemase na

suvo,%

Iskoritenje

Fe,%

Procentualniudio

asortimana %

Obogaenje,

%

Ulazna ruda 69844 58125 46.99 1.84 14.61 16.73 100 100 98.49 100%

Krupni

koncentrat,

APR

7707 6804 53.53 1.56 7.80 11.60 11.03 11.71 13.33 16% 6.54

Sitni

koncentrat,

BPR41608 34544 50.27 2.02 10.76 16.94 59.57 59.43 63.57 84% 3.27

Ukupni

koncentrat49315 41348 50.81 1.94 10.27 16.11 70.61 71.14 76.91 3.81

Mulj 20529 16776 35.14 1.85 29.54 29.39 28.86 21.58 -11.85

ODNOS APR:BPR 16:84 (SA TERCIJARNIM POSTROJENJEM)

2.

AsortimanMasa namokro,

mil t

Masa nasuvo,

mil t

Fe% Mn% SiO2 % H2O%Iskoritenje

mase na

mokro,%

Iskoritenjemase na

suvo,%

Iskoritenje

Fe,%

Procentualniudio

asortimana %

Obogaenje,

%

Ulazna ruda 69844 58125 46.99 1.84 14.61 16.73 100 100 98.49 100%

Krupni

koncentrat,

APR

20775 18606 53.53 1.56 7.80 11.60 29.74 32.01 36.46 45% 6.54

Sitni

koncentrat,

BPR28540 22742 48.58 2.27 12.29 20.01 40.86 39.13 40.45 55% 1.59

Ukupni

koncentrat49315 41348 50.81 1.94 10.27 16.11 70.61 71.14 76.91 3.81

Mulj 20529 16776 35.14 1.85 29.54 29.39 28.86 21.58 -11.85

ODNOS APR:BPR 45:55 (BEZ TERCIJARNOG POSTROJENJA)

Fe.


44/480

II - , 2016

3.2.2.

- 30 7t/h .

. , , , .

. 30 .

. , . () .

, . , .

Ecochem A-1 30 , 30 . 3.

3.


45/480

II - , 2016

3.2.3.

, .(-1mm).

. ,:

SLon 2500, Outotec, // 75 -125 t/h, 200-400m3/h. 15m ,1mm .

4. .

4.

3.2.4.

30% -25m. -25m (-) -, , , ., -.


46/480

II - , 2016

:

Fe, % 45-55 -0.025+0 mm 90%SiO2, % 6-16 -0.5+0.025 mm 10%Mn, %. 2Al2O3, % 1-4

() , .

, 2012. , 1.7 m2, 3.

3.

Pumpanje

mulja

(min)

Presovanje

(min)

Produvavanje

(min)

Ostalo

vrijeme

(min)

Trajanje

ciklusa

(min)

Tokom

pumpanja

(bar)

Tokom

presovanja

(bar)

I 3.0 3.5 1.0 4.0 11.5 3.0 16.0 100 31.8 20 175

II 3.0 3.5 0.0 4.0 10.5 6.0 15.0 70 30.33 21 218

III 3.0 3.5 3.0 4.0 13.5 6.0 16.0 70 30.39 21 158

IV 2.0 3.5 1.0 4.0 10.5 3.0 16.0 90 19 215

I 3.0 3.5 0.0 4.0 10.5 5.7 16.0 100 30.09 20 192

II 3.0 3.0 0.0 4.0 10.0 5.6 15.0 120 27.69 21 229

III 3.0 3.5 0.0 4.0 10.5 5.6 15.0 120 29.8 21 203

IV 3.0 2.5 0.0 4.0 9.5 5.2 15.0 130 30.42 19 238

I 3.0 2.7 0.0 4.0 9.7 5.8 15.0 120 31.86 20 207

II 3.0 3.0 0.0 4.0 10.0 5.5 16.0 120 30.99 21 229

III 2.0 3.2 0.0 4.0 9.2 5.9 15.0 110 31.45 21 232

I 3.0 3.5 0.0 4.0 10.5 5.6 16.0 100 28.75 19 211

II 3.0 3.5 0.0 4.0 10.5 5.7 16.0 100 30.35 17 213III 4.0 3.5 0.0 4.0 11.5 5.6 15.0 100 30.32 23 198

IV 2.0 3.0 0.0 4.0 9.0 5.8 15.0 70 28.38 14 147

I 3.0 3.0 0.0 4.0 10.0 5.1 15.0 100 30.98 16 164

II 3.5 3.1 0.0 4.0 10.6 5.0 15.0 120 31.2 15 159

III 3.5 3.0 0.0 4.0 10.5 3.9 15.0 100 31.29 13 134

6/9/2012 1.4 42

6/16/2012 1.3 25

6/8/2012

1.4 38

1.4 42

Prosjena

debljina

keka

(mm)

Stepen

filtracije

kg/mh

6/7/2012 1.3 34

Udio

vrstog

u

mulju

%

Parametri filtracije (trajanje) PritisakKoliina

ulaznog

mulja

(l)

Vlaga u

keku

(%)

DatumPranjenje

keka

Gustina

ulaznog

mulja

kg/dm

, Bilfinger GHT 2000,11917 l = 11.917 m3, 710.7 m2 103 . , , , 50 , : , , , , , ,

. 5. , 4. .


47/480

II - , 2016

5.

4.

Asortiman

Masa na

mokro,

mil t

Masa na

suvo,

mil t

Fe% Mn% SiO2% H2O%

Iskoritenje

mase na

mokro,%

Iskoritenje

mase na

suvo,%

Iskoritenje

Fe,%

Procentualni

udio

asortimana %

Ulazna ruda 30 24 46,50 1,97 15,55 19,60 100,00 100,00 100,00

Krupni

koncentrat, APR4 3 52,30 1,51 9,09 13,50 13,32 14,33 16,12 19,89

Sitni koncentrat,

BPR16 13 50,78 2,02 10,51 17,00 53,64 55,38 60,47 80,11

Ukupni

koncentrat20 17 51,09 1,92 10,22 16,30 66,96 69,71 76,59

Mulj 10 7 35,94 2,09 27,83 33,04 30,29 23,41

4.

. , . , (10%:90% 45%:55%). , ,

.

, 7t/h, 30.000 t . , ,, 48%, 46.5% Fe.10%.

, . , 1.3 mil t ,


48/480

II - , 2016

-0.025mm 48% Fe. , . , , -.

Acknowledgements

Significant contribution and support to ArceloMittal Prijedor, in the research related to theproject of GMS Processing Plant optimization, has been provided by ArcelorMittal Miningand Mineral Processing Research Centre, Maizieres-les-Metz/France.

[1]

[2]

[3]

[4]

[5]

[6]

Plant Optimization Report, ArcelorMittal Mining and Mineral Processing Research CentreMaizieres-les-Metz, ArcelorMittal Prijedor, Buvac Mine, October 2012Recapitulation of lab tests of hydrocyclone overflow filtration, ArcelorMittal Prijedor,ArcelorMittal Mining and Mineral Processing Research Centre Maizieres-les-Metz, April2012, , ArcelorMittal, 2012, ArcelorMittal , 2014,2015 - - ,ArcelorMittal , 2014

- - , ArcelorMittal, 2014


49/480

II- , 2016


50/480

II - , 2016

1, .

1

...

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.

, ,

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.

.

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1.

,,, , , , .

.

, , , .

. .

, , . . , .

.


51/480

II - , 2016

2.

, , , , , . 1996, 2006, 2010-2015. , , 1 .

1

1996 1.093.325 390.930 127.041 11.920 - - 1.623.216

2006 1.571.082 1.979.575 *512.115 *6.301 - - 4.069.073

2010 1.547.098 2.278.258 794.363 - - -

2011 2.085.640 2.658.219 927.755 31.529 23.383 - 5.703.143

2012 2.037.646 1.935.516 1.087.927 87.204 89.677 -

2013 1.907.499 2.480.622 852.930 105.660 180.967 -

2014 1.750.304 2.272.748 1.211.401 101.612 148.952 -

2015 2.030.832 2.531.303 1.212.406 100.622 165.014 10.000 6.040.177

*

1


52/480

II - , 2016

2

()

1996 1.623.2162006 4.069.073

2011 5.703.143

2015 6.040.177

2

1996 2015

3 2030.

()

()

1996.

()

2008.

()

2030.

390.930 2.074.452 4.650.000 1.093.325 1.765.372 1.750.000

127.041 600.803 2.800.000

11.920 0 600.000

- 0 200.000

1.623.216 4.440.629 10.000.000


53/480

II - , 2016

.

1. , , , (, )(,).

2. 1996. 2015. 1.623.216 6.040.177 .

3. 2030. 10.000.000 .

3.

-. , ( ) .

(ArcelorMittal) 126.059 t 2.941.080 t. 4 3 .

4

() ()

1996 0 2009 1.465.301

*2004 126.059 2010 1.936.500

2005 1.673.418 2011 2.681.3452006 1.888.091 2012 2.947.407

2007 1.613.963 2013 2.927.137

2008 1.481.730 2014 2.941.080

*


54/480

II - , 2016

3

4.

. (Juzural Zolata), (Gross) , . , , . 5 4.

5

()

1996 0

*2005 135.000

2006 30.000

2007 100.000

2008 175.000

2009 110.000

2010 185.000

2011 210.000

2012 240.000

2013 280.000

2014 300.000

2015 320.000

* 4


55/480

II - , 2016

5.

. , , . 2012. . 6 5.

6

***

()

1997 5.000

*2001 10.000-15.000

2011 16.000

**2012 17.290

1 1.700

2014 23.500

2015 22.500

5

6.

. , ( ),

, .

, .

.

, ,

.


56/480

II - , 2016

, . (-), ().

[1] 2030. .,2010. .[2] .[3] , , , , 2004. .

[4] 30 40.000 t 8.000 t , .


57/480

II - , 2016

1, . ,

1

: ,

,

on-line

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, , , , , ,, , , , , , .

O ,, , - , . , ,.

2012 , XX, ,, , -, . XX , , , , , ,

(1).


58/480

II - , 2016

, .-. -, . . , . . : , . .

, . ,. , , 14 . , , (2). , -.

, , , . , "" (2). , , .

, , -, " , ".

. . - , ,. : . (). : , . , (2), .


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II - , 2016

, . , , ., , , -(2, 3, 4, 5).

, , . , , . -: : ; ; ; , ,-, .

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II - , 2016

, ,, () 25 . -, 15 , . 50 2000. ., , , , , .

, , -, . , . .

Raw materials initiative (10) , . :

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II - , 2016

, , , . , ( ), , .

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62/480

II - , 2016

, , , , , , , . . . , , , . , , ,

.. ,, . .

Deming Whitman, 2007. Globalisation of Minerals Industry R & D : , , , . 45-50 50- 60 US $. , : .... : . , , , ". . , : .- , .

, , , , , , .

, , , . . , , ,

, ,.


63/480

II - , 2016

, , . . .

, . . , , (2). -.

[1]

. , XX ,, ,, , , 2014.

[2]

pescanik.net/wpcontent/PDF/ToniDad:TEKOZEMLJI[3] http://www.doiserbia.nb.rs/Globalizacija na Balkanu[4] N. ali,Lj. Andri, N. Magdelinovi, Globalization and development of mineral processing

in small and less developed countries, XV Balcan Mineral Processing Congres, Sozopol,(2013), p.1195-1199

[5] www.nspm.rs/ekonomska-politika/neoliberalni-koreni-svetske-ekonomske-krize.[6] www.efzg.unizg.hrThe Impact of Globalisation on the Technological Development of Small

Countries

[7]

www.globalisationanddevelopment.com[8] www.naturalresources.gr/.../ Globalisation and the Industrial Minerals Industry[9] www.kfbih.comOdrivo Upravljanje Mineralnim Sirovinama[10]

http://ec.europa.eu/growth/sectors/raw-materials/[11] catapa.be/en/mining Mining and globalization[12] www.irpps.cnr.it/en/research Daniele Archibugi and Carlo Pietrobelli, The Globalisation of

Technology and Its Implications for Developing Countries[13] http://www.doiserbia.nb.rs/Globalizacija na Balkanu

[14] www.bergforsk.se/wpcontent.TheglobalizationofmineralindustryR&D,[15]

Calic N.,A Brief look on the long history of metalic ores processing in the BALKANS, XVIBalkan mineral processing congress, Belgrade, June 2015. P 21-29,

[16] SMP, Society of Mining Professors/Societaet Der Berbaukunde, Global Minerals education

and Society of Mining Professors/Societaet der Berbaukunde: A Vision for the Future and aPlan of Action, Report submitted to the Society by the Planning Subcommittee, March, 2004.

[17]

www.goodreads.com Politics Political Science; The Shock Doctrine: The Rise of DisasterCapitalism by Naomi Klein
http://www.doiserbia.nb.rs/http://www.nspm.rs/ekonomska-politika/neoliberalni-koreni-svetske-ekonomske-krizehttp://www.efzg.unizg.hr/http://www.globalisationanddevelopment.com/http://www.naturalresources.gr/.../%20Globalisation%C2%A0and%20the%C2%A0Industrial%C2%A0Minerals%C2%A0Industry%C2%A0http://www.kfbih.com/http://www.kfbih.com/loc/default.wbsp?p=17&n=1234&naslov=Odr%9Eivo%20Upravljanje%20Mineralnim%20Sirovinama%20-%20projekat%20%20SARMahttp://www.google.ba/url?sa=t&rct=j&q=globalization%20and%20mining&source=web&cd=1&cad=rja&ved=0CC4QFjAA&url=http%3A%2F%2Fcatapa.be%2Fen%2Fmining&ei=UZjDUKb6Kqb14QT_84DYCg&usg=AFQjCNEEFmQ5KvRy2yUjK4Z70k2d7SdNlghttp://www.doiserbia.nb.rs/http://www.doiserbia.nb.rs/http://www.google.ba/url?sa=t&rct=j&q=globalization%20and%20mining&source=web&cd=1&cad=rja&ved=0CC4QFjAA&url=http%3A%2F%2Fcatapa.be%2Fen%2Fmining&ei=UZjDUKb6Kqb14QT_84DYCg&usg=AFQjCNEEFmQ5KvRy2yUjK4Z70k2d7SdNlghttp://www.kfbih.com/loc/default.wbsp?p=17&n=1234&naslov=Odr%9Eivo%20Upravljanje%20Mineralnim%20Sirovinama%20-%20projekat%20%20SARMahttp://www.kfbih.com/http://www.naturalresources.gr/.../%20Globalisation%C2%A0and%20the%C2%A0Industrial%C2%A0Minerals%C2%A0Industry%C2%A0http://www.globalisationanddevelopment.com/http://www.efzg.unizg.hr/http://www.nspm.rs/ekonomska-politika/neoliberalni-koreni-svetske-ekonomske-krizehttp://www.doiserbia.nb.rs/


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[1] , ., , , , ., , . . VIII''2009 ''. , 126133, 2009.

[2] , ., , . . VI Me ''2013''. , . 171180, 2013.

[3] , ., , . (Festuca arrundinacea Schreb.) . , Vol. 12, br. 1, . 5766, 2011.

[4] Mali, N., Goli, Z., Markovi, M. Changes in the Adsorption Complex of Rekultisol Underneaththe Seeded Grasslands. 9th Congress of the Soil Scienece Society of Bosnia and Herzegovina,Book of Apstrakt, 5253. Mostar - B&H, 2015.

[5] , . - ( ). , 2015.

[6] Thorne, M. E. Calcareous Compacted Mine Soil in Southeast Ohio: A Prairie Grass Habitat.Environmental Science Graduate Program. Dissertation. The Ohio State University.http://etd.ohiolink.edu/view.cgi, 2010.

[7] Skousen, J., Zipper, C. E. Revegatation Species and Practices. Powell River Project (ReclamationGuidelines for Surface-Mined Land). Virginia Cooperative Extension, Publication 460122.www.ext.vt.edu, 2010.

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, . - . ( ). , 2010.

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[10], ., , . e (riticum aestivum L.). , 15 (3), 255-266, 2014.

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[12], ., , ., , . . , 15 (3), 245-254, 2014.

[13]Resulovi, H., ustovi, H. Technosols - Development, Classification and Use. AgriculturaeConspectus Scienificus, Vol. 72, No. 1, 13-16, 2007.

[14], ., , , , . . II ''- 2011 ''., 534539, 2011.

[15]IUSS, ISRIC, FAO. Word Reference Base for Soil Resources: First update 2007, 92-93, 2006.[16]

. '''' ., 2010.

[17] . '''' 2016-2012. . , 2015.
http://etd.ohiolink.edu/view.cgihttp://www.ext.vt.edu/http://www.ext.vt.edu/http://etd.ohiolink.edu/view.cgi


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technology.com[3] C4SE: ENGINEERING LABOUR MARKET in Canada-Projections to 2025, ,

2015, www.engineerscanada.ca[4] http://lmip.gov.au/Labour Market Information Portal[5] 2015. ,

[6] www. nezavisne.com/ekonomija/analiza[7] 20162021
http://www.mining-technology.com/http://www.mining-technology.com/http://www.engineerscanada.ca/https://www.google.ba/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwiAlcvH8oTNAhWJchQKHTWPB5AQFggqMAA&url=http%3A%2F%2Flmip.gov.au%2Fdefault.aspx%3FLMIP%2FIndustryInformation%2FMining&usg=AFQjCNFQFyKaFyb9dWd_uP8teYFTu1n3yAhttps://www.google.ba/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwiAlcvH8oTNAhWJchQKHTWPB5AQFggqMAA&url=http%3A%2F%2Flmip.gov.au%2Fdefault.aspx%3FLMIP%2FIndustryInformation%2FMining&usg=AFQjCNFQFyKaFyb9dWd_uP8teYFTu1n3yAhttp://www.engineerscanada.ca/http://www.mining-technology.com/http://www.mining-technology.com/


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A SIGNIFICANCE OF THE APPLICATION OF NEW STRATEGIES

AND TECHNOLOGIES IN THE EXPLOITATION OF COAL LAYERS

IN THE REPUBLIC OF SRPSKA AND SERBIA

1, . 2, . 3, . 4

: . . 8 , .

. . .

: , , , .

bstract:Mineral and energetic resources in the Republic of Srpska are significant. This is a study on

the field of energetic mineral raw materials (coal) in the last decades. Production stagnated and there

was a fall in production in some mining fields and in the other there was a development. The field of

the underground exploitation had its deteriorating process in majority of the criteria. The examples of

it in the underground exploitation in Serbia in JP PEU Resavica (with 8 mines) in the mine copper

basin RTB Bor, which are now in a very difficult situation where the new solutions are being found for

their further survival. Open-pit mining especially of the energetic raw materials had a relatively better

development in the majority of the coal basins in the Republic of Srpska and Serbia because of the

better conditions for the exploitation and production of the energy in thermal power plants.

In this paper the basic guidelines are indicated how to overcome the difficult conditions in mining of

the Republic of Srpska through the application of the new technologies of the exploitation.

1 , , -mail:

[email protected] , , -mail:

[email protected] , , -, -mail:

[email protected]

, , -, -mail: [email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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The examples are given as well as other mining countries richer than us which search for the best

solutions.

Key words:New strategy, new technology, mechanization, new technologies, mechanization andautomation in the mines, alternative technologies.

1.

1.1.

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, , , , , - .

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) ( ) .

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j "" . " -" [5].

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) (500 m).

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3.1.

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. ( 1000m)

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.


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8.200 / ( 16.894 / ), Zafiowka 3.400 / ( 4.600) Jas -Mos 3.000 / ( 5.050 /).

,

.

, -, :1. 30%

.2. 500 m ,

1800 m 220 2/3 .

3. - , 1 m .

4. . , .

4. ()

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- ,( 10.000 ) , .

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.

ITERATURA

[1] . , . , . , . :

, 2/2002, , , , 2002.

Documents

II Rudarsko Geološki forum, Prijedor 2016