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MASTER'S THESIS Improvement of blast-induced fragmentation and crusher efficiency by means of optimized drilling and blasting in Aitik Ali H. Beyglou Master of Science (120 credits) Civil Engineering Luleå University of Technology Department of Civil, Environmental and Natural Resources Engineering


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Improvement of blast-inducedfragmentation and crusher efficiency by

means of optimized drilling and blasting inAitik

Ali H. Beyglou

Master of Science (120 credits)Civil Engineering

Luleå University of TechnologyDepartment of Civil, Environmental and Natural Resources Engineering

Improvement of blast-induced fragmentation and crusher efficiency by means of optimized drilling and blasting in Aitik.

Ali H. Beyglou

Division of mining and geotechnical engineering

Department of civil, environmental and natural resources engineering

Luleå University of Technology

September 2012


The thesis project presented in this report was conducted in Boliden’s Aitik mine;

thereby I wish to gratefully thank Boliden Mines for their financial and technical support.

I would like to express my very great appreciation to Ulf Nyberg, my supervisor at

Luleå University of Technology, and Evgeny Novikov, my supervisor in Boliden for their

patient guidance, technical support and valuable suggestions on this project. Useful advice

given by Dr. Daniel Johansson is also greatly appreciated; I wish to acknowledge the

constructive recommendations provided by Nikolaos Petropoulos as well.

My special thanks are extended to the staff of Boliden Mines for all their help and

technical support in Aitik. I am particularly grateful for the assistance given by Torbjörn

Krigsman, Nils Johansson and Peter Palo. I would also like to acknowledge the help provided

by Sofia Höglund, Torbjörn Larsson, Jansiri Malmgren and Lisette Larsson during data

collection in Aitik mine.

I would also like to thank Forcit company for their assistance with the collection of the

data, my special thanks goes to Per-Arne Kortelainen for all his contribution.

Finally my deep gratitude goes to my parents for their invaluable support, patience and

encouragement throughout my academic studies.

Luleå, September 2012

Ali H. Beyglou


Rock blasting is one of the most dominating operations in open pit mining efficiency.

As many downstream processes depend on the blast-induced fragmentation, an optimized

blasting strategy can influence the total revenue of a mine to a large extent.

Boliden Aitik mine in northern Sweden is one of the largest copper mines in Europe.

The annual production of the mine is expected to reach 36 million tonnes of ore in 2014; so

continuous efforts are being made to boost the production. Highly automated equipment and

new processing plant, in addition to new crushers, have sufficient capacity to reach the

production goals; the current obstacle in the process of production increase is a bottleneck in

crushers caused by oversize boulders. Boulders require extra efforts for secondary blasting or

hammer breakage and if entered the crushers, they cause downtimes. Therefore a more evenly

distributed fragmentation with less oversize material can be advantageous. Furthermore, a

better fragmentation can cause a reduction in energy costs by demanding less amounts of

crushing energy.

In order to achieve a more favorable fragmentation, two alternative blast designs in

addition to a reference design were tested and the results were evaluated and compared to the

current design in Aitik. A comparatively large bench was divided to three sections with three

different drill plans, which led to different specific charges in each section. The sections were

drilled in patterns of 6x9 m, 7x9 m and 7x10 m of burden and spacing; planned specific

charges of the sections were 1.17 kg/m3, 1.02 kg/m3, and 0.91 kg/m3 respectively. Similar to

the current drill plan in Aitik, the section with 7x9 m ( 1.02 kg/m3 specific charge) was used

as the reference for results comparison. The drilling and charging processes were monitored

carefully and the post-blast parameters were measured accordingly. Laser scanning was used

to measure the swelling of the sections and two different methods of image analysis were

utilized to evaluate the fragmentation of the rock for each section. Drilling log data (MWD)

were analyzed to evaluate the hardness of the rock; energy consumption log of the crusher

was also analyzed and all the data was collected in a single database. VBA (Visual Basic for

Applications) programming language was embedded within data spreadsheets to correlate the

mentioned data to the coordinates of the rock by means of Minestar logs, which include both

timestamps and coordinates of all machinery e.g. shovels and trucks.

The results of the test show significant improvements in fragmentation and oversize

material percentage in the section with 6x9 m drill plan (1.17 kg/m3). The advantage of 6x9

m plan was confirmed by 52% higher swelling, 66% lower oversize material and 26% lower

crushing energy compared to the reference section. The section with 7x10 m drill plan (0.91

kg/m3) also showed theoretically acceptable results; however, the deviations from reference

were not as large as formerly mentioned section. The swelling had a decrease of 8%

compared to the reference section and the percentage of oversize material and crushing

energy were increased by 16% and 2% respectively.

Presented results are based only on technical aspects and do not include the costs of

drilling and charging. Thus, in order to evaluate the drill plans in practice an economical

evaluation of the sections should be conducted. Also a confirmation test with more accurate

geology explorations is recommended.

Finally, upon the request of Boliden Mines, a short report on the usage of Air-decking

technique in Aitik is enclosed as an appendix. The report includes a brief introduction to air-

decking and discusses practical solutions to apply this technique in Aitik.

TABLE OF CONTENTS 1 INTRODUCTION ............................................................................................................... 1

1.1 Aims and objectives .................................................................................................. 2 2 THEORY AND BACKGROUND ...................................................................................... 4

2.1 Rock breakage by blasting ........................................................................................ 4 2.2 Mechanical properties of rock mass .......................................................................... 6 2.3 Bench blasting ........................................................................................................... 8 2.4 Particle size distribution .......................................................................................... 10 2.5 Influence of blasting on downstream processes ...................................................... 12

3 AITIK MINE ..................................................................................................................... 13 3.1 Drilling and blasting ................................................................................................ 14 3.2 Loading and hauling ................................................................................................ 16 3.3 Crushing and grinding ............................................................................................. 17

4 TEST BLAST .................................................................................................................... 18 4.1 Description .............................................................................................................. 18 4.2 Data quality and constraints .................................................................................... 22

4.2.1 Drilling (MWD) ................................................................................................... 23 4.2.2 Charging .............................................................................................................. 25 4.2.3 Shovel .................................................................................................................. 27 4.2.4 Trucks (Minestar) ................................................................................................ 27 4.2.5 Split-Desktop ....................................................................................................... 28 4.2.6 FragMetrics ......................................................................................................... 30 4.2.7 Crusher ................................................................................................................ 31

4.3 Analysis strategy ..................................................................................................... 33 5 TEST RESULTS ............................................................................................................... 35

5.1 Hardness of the rock (MWD) .................................................................................. 35 5.2 Swelling ................................................................................................................... 37 5.3 Digability ................................................................................................................. 39 5.4 Fragmentation .......................................................................................................... 40

5.4.1 Split-Desktop ....................................................................................................... 40 5.4.2 FragMetrics ......................................................................................................... 45

5.5 Crusher efficiency ................................................................................................... 46 6 DISCUSSION AND CONCLUSIONS ............................................................................. 48 7 RECOMMENDATIONS AND FURTHER STUDIES .................................................... 51 REFERENCES ........................................................................................................................ 53 ADDITIONAL BIBLIOGRAPHY ......................................................................................... 54 APPENDIX I: Fragmentation analysis of FragMetrics software APPENDIX II: An introduction to Air-decking in Aitik



Open pit mining is one of the most utilized methods of ore extraction worldwide. Cost-

effectiveness, mechanical ease and safer environment are some of the advantages of open pit

mining over other mining methods, in addition to that, its potential for large production

volumes and low cost of recovery allows low-grade ore bodies to be extracted feasibly.

Drilling and blasting is, by far, one of the main operations in open pit mines, affecting

the total revenue of the mine to a large extent. Pre-blast costs, such as drilling and explosive

expenses, are directly influenced by blast design; post-blast parameters are also affected by

the outcome of the blast; secondary blasting, loading and hauling, crusher throughput, and

grinder efficiency are related to blast-induced fragmentation of the ore (Nielsen and Lownds

1997, McKee et al. 1995).

Blasting is the most energy efficient stage in the comminution process. According to

Eloranta (1997), blasting has an energetic efficiency of 20% to 35%, which is relatively high

compared to respectively 15% and 2% efficiency of crushing and grinding. High efficiency

offers the blasting stage a strong potential for optimization of the overall comminution

process, however, the operations included in the comminution process were treated

individually for a long time and the optimizations were merely limited to the outskirts of each

operation. A more recent approach to optimization is called ‘Mine-to-Mill’, provided by

Julius Kruttschnitt Mineral Research Centre in 1998 (JKMRC 2012). Mine-to-Mill, in short,

is ‘an approach that identifies the leverage that blast results have on different downstream

processes and then optimizes the blast design to achieve the results that maximize the overall

profitability rather than individual operations’ (Grundstrom et al. 2001). According to Mine-

to-Mill concept, blasting should be designed in a way that satisfies the overall requirements of

the comminution process, including haulage, crushing and grinding altogether.


Research works by Eloranta (1997), Kojovic (2005), Ouchterlony (2003 and 2005)

and Ouchterlony et al. (2010) show a meaningful relation between blast properties and

efficiency of crushing and grinding. Therefore the optimization of blasting should not only

include the size distribution of blasted rock, but also consider the crusher throughput and

grinder energy consumption.

The importance of blasting has also urged the necessity of reliable monitoring systems

to develop. Fragmentation is a key factor in the comminution process and image analysis has

been the most utilizable method of fragmentation measurement so far (Chiappetta 1998).

Developments in that field have led to systems able to measure the fragmentation

continuously during mining; such systems, together with well-calibrated measurements of

throughput and energy consumption in crusher and grinder, provide an appropriate database

to optimize the process.

1.1 Aims and objectives

The main goal of the current project is to find an economically viable alternative blast design

to provide an improved fragmentation as well as an increase in the energy efficiency of the


Constant efforts are being made in the Aitik mine to optimize the production process;

accordingly, blast-induced fragmentation is of significant importance as a major role player in

such optimization. Boliden Mines implemented an expansion of operations project (Aitik 36)

during the period of 2006 to 2010. Pushbacks at the southeastern, northeastern and western

sides of the pit resulted in trebling of ore reserves from 200 Mt to 600 Mt, as well as an

extension in mine life from 2016 to 2025 and the ability to excavate down to 600 m depth. In

2010 a new modern processing plant has been inaugurated in accordance to Aitik 36


expansion project, aiming to increase the annual production up to 36 Mt until 2014; but

presently, the crusher, which is directly influenced by fragmentation of blasted rock, is a

bottleneck in comminution process.

Large number of oversized boulders requires high cost and effort for secondary

blasting; in addition to that, accidental throw of oversized boulders in the crusher opening

causes downtime in the crusher, which creates a bottleneck in the production. A solution to

such problem is to modify the blasting parameters in a way that improves the size distribution

of the fragmented rock. The alteration in parameters should not only result in fewer boulders

but also in an increase in the energy efficiency of the crusher.



2.1 Rock breakage by blasting

The entire blasting act takes only a few seconds in scale of time. However, several events take

place in different segments of those seconds. Once initiated, the explosive 1 releases an

enormous amount of energy through chemical reactions, resulting in high-pressure gases in

the blast hole which can amount to and exceed 10 GPa. The high pressure of gases is not, in

and of itself, the only cause of the breakage; the rapidity of the reaction plays the leading role

(Langefors and Kihlström 1967).

Upon initiation, the reaction advances at a rate (Velocity of Detonation, VOD) of

approximately 2000-6000 m/s throughout the explosive. Considering the 15-20 m length of a

normal blast hole, one can easily realize that the reaction takes place within thousandths of a

second. The rapid reaction leads to an almost instantaneous pressure rise in the hole, which

produces a shockwave in the rock, traveling at a speed of 3000-5000 m/s. The high pressure

expands the walls of the hole and the area adjacent to the drill hole shatters as a result of vast

amounts of tangential strains and stresses. The shattered area around the hole, with rose

shaped cracks towards outside of the hole, is the first platform for fracturing (Esen et al. 2003).

See figure 2.1.

1 In this report, the word “Explosive” refers to non-military, civil explosive materials used in mining industry.


Figure 2.1: Fractured area around the blast hole, the so-called Rose of cracks, After Esen et al. (2003).

The shockwave travels at such high speed that the initial cracks form within a few

milliseconds. According to wave propagation concept (Hustrulid 1999), the positive pressure

of shockwave falls rapidly to negative values, which implies a change from compression to

tension. Since rock is generally more resistant to compression than to tensile strain, the initial

radial cracks are the results of tensile forces acting on the area around the hole.

During the first stage there is practically no breakage in the rock other than the radial

cracks. The main breakage occurs after the shockwave reaches the free face of the rock and

reflects as a tensile wave, such phenomenon gives a rise to the tensile strains and

consequently extends the cracks throughout the rock. This stage is called Scabbing (Langefors

and Kihlström 1967).

The scabbing and radial cracks are both effects of the shockwave; the last stage of

breakage is under the influence of pressurized gases produced by the blast; this stage is

considerably slower than the first two. The high-pressure gases in the blast hole, kept inside

by the stemming, pressurize the borehole and apply a radial compressive stress perpendicular

to the borehole; the compressive stress is large enough to initiate new cracks and extend the


existing cracks. The crack expansion outspreads through the rock and results in breakage. The

overall displacement of the rock mass prior to gas action is very little; the gases not only

extend the cracks, but also exert a pushing force to move the broken rock forward (Langefors

and Kihlström 1967).

A successful, complete breakage takes place when the amount of explosive and the

geometry of the blast e.g. burden, spacing, height, are balanced in a way that the cracks

expand all the way to the free face and gases push the rock forward to form a well-swollen

pile; so it is critical to find the appropriate proportions of these factors based on the rock

strength, fracturing, and explosives characteristics in order to reach an adequately broken and

swollen rock pile.

2.2 Mechanical properties of rock mass

The strength of rock can be defined by many parameters, e.g. compressive and tensile

strength. The large difference between intact rock strength and rock mass strength cause many

uncertainties in large-scale mining activities. Figure 2.2 shows the difference between rock

mass and intact rock; the mechanical behavior of rock mass is heavily affected by

discontinuities, varying in a wide range from microscopic cracks to regional faults. In

addition to that the direction of the load and confinement conditions effect the behavior of the

rock mass; high confinement pressure turns brittle failure to ductile and due to closure of

micro cracks Young’s modulus increases (Brady and Brown 1993).


Figure 2. 2: Schematic difference of intact rock and rock mass, after Scott et al. (1996).

In addition to that, the failure of rock includes an element of creep, which means the

loading rate effects the strength of the material (Bergman 2005). Crushing and grinding of

rock are performed through static loading of the rock. However, blasting exposes the rock to

both static and dynamic loading due to rapid explosive reactions. Such dynamic loading

exposes the rock to high loading rates, which results in higher compressive strength (Persson

et al. 1994) and increased Young’s modulus of the rock (Bergman 2005).

The complexity of rock mass characterization for blasting purposes leads to the

conclusion that analytical solutions are not possible. As of yet, empirical measures have been

the most useful tools to classify rock masses. The rock constant, c, is one of the most utilized

tools in blast designs. Rock constant is a measure of the amount of explosives needed to break

one cubic meter of rock and it is determined by controlled trial blasts in a vertical bench

(Langefors and Kihlström 1967).


2.3 Bench blasting

Achieving a well-distributed particle size is the main goal of blasting, so that the rock can be

handled efficiently in post-blast processes, e.g. loading and crushing. The outcome of blast is

influenced by several parameters; mechanical properties of rock mass, geometry of blast holes,

type and amount of explosives, initiation pattern and delay times are some of the key factors

in blast design. A brief terminology of bench blasting geometry is presented in Figure 2.3.

Figure 2.3: Bench blast geometry and terminology, Bergman (2005).

Specific charge, in addition to the geometry, is a key factor in bench design

(Langefors and Kihlström 1967). The specific charge, q, represents the explosives

consumption per cubic meter of rock (or per tonne rock). Specific charge varies based on

explosive and rock mass characteristics, see equation 2.1.



= (2.1)


q: Specific charge (kg/m3)

Q: Total explosive per hole (kg)

B: burden (m)

S: Spacing (m)

H: Bench height (m)

Burden, B, is the distance between the rows and spacing, S, is the distance between

the holes in a row. Several empirical equations are provided in the textbooks for calculation of

the burden; Langefors and Kihlström (1967) provided a well-known formula for calculation

of maximum burden, equation 2.2.

( )BSfc


=33max (2.2)


D = blast hole diameter (mm),

p = explosive density (kg/dm3)

E = weight strength of explosive (%)

B = burden (m),

c = rock constant (kg/m3)

f = degree of confinement, 1 for vertical holes.

Other parameters are basically calculated by empirical rules of thumb, such as

(Persson et al. 1994):

3.1=BS (2.3)


3.0max ×= BU (2.4)

)(05.1 UHL += (2.5)

These empirical relationships are usually modified depending on the size and characteristics

of the blast.

2.4 Particle size distribution2

The results of a production blast are mainly presented by fragmentation of the broken rock.

The fragmentation is described in terms of geometrical characteristics of the particles i.e. size,

angularity or roundness. The cumulative size distribution function, CDF, provides a complete

description of the former. It is either obtained from physical sieving of the material, which is

very costly in large-scale blasts, or by non-physical sieving methods such as image analysis.

The CDF is the ‘fraction of mass P passing a screen with a given mesh size x.’(Ouchterlony

2003). Percentage of passing material from each mesh, P(x), varies between 0-100%, see

Figure 2.4.

2 Mainly based on the SWEBREC report by Ouchterlony (2003).


Figure 2.4: Cumulative size distribution curve, Ouchterlony (2003).

Depending on the purpose of the analysis, several distinctive quantities are extracted

from the curve, here follows some:

X50 = a measure of the average fragmentation, i.e. mesh size through which half of the

material passes, X50 is a central production measure.

XN = other percentage related block size numbers in use. N=20, 30, 80, 90 etc.

PO = percentage of fragments larger than a typical size XO. PO is related to e.g. the

handling of big blocks by trucks or the size of blocks that the primary crusher cannot


PF = percentage of fine material smaller than a typical size XF.

In large-scale production sites the focus is on the most important of these, which in

Aitik case is PO, due to problems caused by boulders at the crusher feed.


2.5 Influence of blasting on downstream processes

The effect of blasting on subsequent operations has drawn a great deal of attention in recent

years. In the past, the only criterion for blast results was the ability of excavation and hauling

equipment to handle the blasted rock, but mining economy demands high production

capacities as well as efficiency of costly operations. Since crushing and grinding consume

enormous amounts of energy, the effect of blasting on efficiency of these operations is

undoubtedly important.

The effect of blasting on fragmentation is assessed in two different aspects: Seen and

Unseen. The size distribution of blasted fragments is the “seen” part of blasting results, which

can be measured quantitatively by sieving or image analysis techniques. The “unseen” effect

of blasting is the fracture generation within the fragments, these fracture can be classified as

either macrofractures or microfractures. Macrofractures are comparatively large and can be

seen on the surface of fragments; but microfractures are only seen through a microscope

(Workman and Eloranta 2003).

The production and downtime of the crusher are under direct influence of the “seen”

effect of blasting; oversize fragments cause a reduction in primary crusher throughput and

lead to more downtime for clearing the crusher bridging (Workman and Eloranta 2003). On

the other hand, the “unseen” aspects of fragmentation influence the energy consumption of

the crusher. Therefore, it is very important to assess the effect of blasting on the energy

consumption of the primary crusher in addition to the fragments’ size distribution.

The degree of dependency of crushing efficiency on macro and microfractures is not

presently clear; but studies and field tests by Eloranta (1995), Workman and Eloranta (2003),

Ouchterlony (2003) and Ouchterlony et al. (2010) confirms that fracturing of the fragments,

caused by heavier blasting, leads to lower energy consumptions in crushing and grinding




Aitik open pit mine is situated outside the city of Gällivare in northern Sweden. The orebody

consists of low grades of copper, gold and silver. The production started with two million

tonnes of ore in 1968 and gradually increased to 31.5 Mt in 2011; the production level is

expected to reach 36 Mt in 2014.

The pit is 3 km long, 1.1 km wide and 425 meters deep; the orebody dips 45° towards

west and mainly consists of metamorphosed plutonic, volcanic, and sedimentary rocks with

various strengths.

Investigations by both Sjöberg (1996) and Bergman (2005) on rock strengths in Aitik

show fairly similar results. Muscovite schist is the weakest rock with an average strength of

64 MPa and Pegmatite is the strongest rock with a 141 MPa compressive strength. Biotite

schist and Biotite gneiss were similarly approximated to have strengths of 88 and 121 MP


The utilized method of excavation in Aitik is pallet mining, in which the ore is

removed in form of horizontal slices. The comminution process is shown in figure 3.1; after

drilling and blasting the ore is loaded into trucks and hauled to the in-pit crusher. Once

crushed, a conveyor belt transports the ore to two ore piles that feed the grinding mills. Later

the grinded ore goes through chemical processes and finally the produced concentrate is

transported to smelter by railway.


Figure 3. 1: Processes involved in mining in Aitik, after Bergman (2005).

3.1 Drilling and blasting

The typical drill plan presently used in Aitik consists of 311mm production holes and 127 and

152mm holes for contour blasting. As seen in figure 3.2, production holes are drilled in

accordance to 7m burden and 9m spacing. Contour holes are drilled with 4 and 5 meters

spacing for first and second row respectively, the rows are distant 4.5m from each other and

6m from first production row. Standard benches are 15m high and blast holes are

approximately 2m sub-drilled.


Figure 3.2: Current design of bench drilling in Aitik.

Four Atlas Copco pit viper PV 351 drill rigs are used for production drilling. The rigs,

equipped with GPS and Terrain for Drilling3 system, are of the most advanced blast hole

drills on the mining market. The coordinates of holes are uploaded to the rig and the rig

navigates to the precise coordinates of each hole using GPS. With 56700 kg of bit load and up

to 107.6 m/min of air at 758kPa, the vipers provide a high capacity of fast drilling. The MWD

system logs all the drilling data, such as torque, penetration rate, feed pressure etc. The logged

data will be analyzed and used for interpretation of the properties of the penetrated rock mass

e.g. hardness, fracturing and hydraulic conditions.

Emulsion explosive is used as the main charge in blast holes; it has an average VOD

of 5700 m/s and is of 1350 kg/m3 density. The emulsion matrix is made in a nearby factory.

Special trucks carry the emulsion matrix, Ammonium Nitrate, diesel and water to the benches.

3 Formerly known as AQUILA™


The trucks are equipped with a system to mix the matrix with diesel and AN beforehand

charging. The temperature of the contents, as well as the mixture proportions and volume of

the explosive filled in each hole are set through the computerized system of the mixing trucks.

The current specific charge of production blasting in Aitik is 1.02 kg/m3, which varies from

time to time depending on geology and production requirements.

Nonel Unidet system is used to detonate the holes. Two boosters combined with two

detonators are placed at the bottom of each hole to assure the detonation of the emulsion, the

boosters and detonators are of types Dyno 1.7 and Nonel U-1000 respectively. The coupling

takes place after plugging the holes with about 5.5 meters of crushed stemming material; the

holes are detonated with 176 ms of delay between the rows and 42 ms delay between the

holes in a row.

3.2 Loading and hauling

Four shovels and 30 trucks of various capacities are used to load and haul the blasted rock.

All vehicles are equipped with Minestar system. Minestar is an integrated operations and

mobile equipment management system; Tracking ore and waste, locating the vehicles and

managing the schedule and assignments of the fleet operations are some of the capabilities of


Presently one of the shovels, of type P&H 4100C, is equipped with a camera installed

on the boom. The camera is part of Fragmetrics™ fragmentation measurement system; it

captures photos of the bucket every two minutes. The photos are analyzed with Fragmetrics

image analysis software to estimate the fragmentation curve of the loaded rock.


3.3 Crushing and grinding

The in-pit crusher, Allis-Chalmers Superior 60-109, does the main part of primary crushing of

the main pit rock. It is situated at the 165 m level and consists of two primary gyratory

crushing stations as well as overland conveyors and feeders. The system has a capacity of

8000 t/h and will transport the ore 7 km. At downtimes, or during maintenance periods, two

crushers on the surface are used. The main crusher’s opening is 152 cm in diameter and the

lower part of the mantle has a diameter of 277 cm. Depending on ore properties, the coarsest

boulders’ size after crushing varies in range of 35 to 40 cm.

The crushed ore is transported to two stockpiles on a conveyor belt. The total capacity

of the stockpiles provides 16 to 20 hours of full production in the mill, i.e. 50000 tonnes.

The grinding process is operated through five grinding lines in three grinding sections.

Each grinding line consists of a primary autogenous mill and a secondary pebble mill. The

process is a close chain, a screw classifier feeds the coarse material back to the primary mill

and pebbles are extracted from the primary mill and fed to secondary mill, Figure 3.3.

Figure 3. 3: Milling process of the ore, Bergman (2005).

Finally the grinded ore is transformed into concentrate by processes of flotation,

thickening, dewatering and drying. The concentrate is then transported by railway to

Rönnskär smelter in the city of Skelleftehamn.



4.1 Description

A production bench, named S1_210_13, with a volume of 774000 m3 was assigned for the

test; it was situated at the western wall of the pit at 210 m level. The bench was divided to

three smaller sections, of which one was used as reference. Hereinafter the letters A, B and C

are referred to these sections. Figure 4.1 shows the bench; a drilling plan of 6 m burden and 9

m spacing was assigned to section A. Section B, with the currently used drill plan (7 m

burden and 9 m spacing), was the reference for further comparisons; the middle section was

chosen as reference in order to minimize the effect of geological discontinuities in the blast

results. Section C was ascribed a wider drill plan with respectively 7 and 10 m of burden and


The test bench consisted of a total number of 668 holes; average planned depth of

holes was 16.2 meters of which 1.2 m was sub-drilling. The planned specific charges were

1.17, 1.02 and 0.91 kg/m3 for sections A, B and C respectively. A stemming length of 5.5

meters was also planned for all holes; gravel of size 5-8 cm was used as stemming material.

During the drilling, some practical issues regarding neighbor benches and machinery

led to a change of plans; a part of section A was omitted from the test bench and scheduled

for the next round. The omitted part is shown with red rectangle in Figure 4.1.


Figure 4. 1: Test bench and drilling patterns.

The bench mostly consists of Muscovite and Biotite Gneiss. Two dykes of Biotite cut

through the bench diagonally, a large part of an Amphibolite Gneiss dyke also cuts the

southeastern edge of the bench (Figure 4.2). Although the geology map does not show any

Pegmatite dyke within the bench area, their existence cannot be discarded for sure as the

precision of explorations are not so high.


Figure 4. 2: Geology of the test bench.

Except the drill pattern, all the blast parameters such as emulsion density, hole depth,

sub-drill etc. were kept unchanged in order to have a parametrically controlled test. Drilling

and charging processes were also controlled and monitored to avoid fortuitous errors.

Nonel Unidet system was used for initiation of the blast. The initiation plan is shown

in Figure 4.3. The southward direction of the blast was decided based on the direction of rock

structure as well as loading availability. The blast initiated at the northeast corner of the bench

spreading towards southwest. A delay of 176 ms was used between the holes and each row

was delayed 42 ms from previous one. As a result of smaller free face for the blast at the

northwestern part of the bench, shorter delays of 67 and 109 ms were introduced for a

smoothly swollen rock pile. To prevent detonation failures, two detonators and two boosters

were used for each hole.


Figure 4. 3: Initiation pattern of the blast holes; the initiation starts at the upper left part in the figure.

The blast itself was filmed using a high-speed camera so the initiation of all holes

could be confirmed. Once blasted, the surface of the bench was laser-scanned to evaluate the

swelling of the rock in three sections.

The rock was photographed continuously during loading. The Fragmetrics camera,

installed on the boom of one of the shovels, photographed the bucket every two minutes. A

10-megapixel camera, Nikon D3000 equipped with a 300 mm tele lens, was also used to

manually photograph the bed of loaded trucks.

To estimate the fragmentation of blasted rock two different softwares were used:

FragMetrics™ and Split-Desktop™. Fragmetrics was used to analyze the photos taken by its

associated camera; manually taken photos were used for Split-Desktop. The Fragmetrics

camera was calibrated in accordance to the width of the shovel bucket (460 cm); no further

adjustments were needed since the position of the camera was fixed. However, manually


taken photos could not be shot from exact positions, so photos were taken from a suitable

level depending on the location of each truck, pictures are shot from an angle which

minimizes the optical distortions in the rock pile. The width of the flatbed of trucks was used

as the scale for size distribution analysis.

To obtain a consistent correlation between the crusher throughput and fragmentation,

the measurements required to be obtained from the identical rock. In order to track the ore

from the bench to the crusher, timestamps were attached to photos. The manual camera, as

well as Fragmetrics camera, was synched to the clock of Minestar system, so the photos could

be linked to certain times of loading and crushing.

By estimating the average time delays for the ore between unloading and entering the

crusher, the crusher throughput could be linked to a certain set of photos. Thus, a size

distribution curve is available for each value of throughput. The location of shovel, obtained

from Minestar, shows the location of the loaded ore and correlates this relationship to one of

the three sections of the bench.

To avoid mixtures of the ore in the crusher, all the trucks were assigned to load the ore

only from the test bench during data collection, so the crusher was only fed with the ore from

the test bench and no ore mixing took place.

4.2 Data quality and constraints

A variety of data sets are involved in the process of correlating pre-blast measurements to

post-blast parameters, each data set is obtained from a different source, including its

systematic errors. In addition to that, each source has a specific chance of failure, which

causes loss in the data and/or large errors. Thus, the necessity of an appropriate analysis


strategy based on the availability and quality of the data is inevitable. Following sections

briefly describe some of the sources, their systematic errors and availability of their data.

4.2.1 Drilling (MWD)

Drill rigs in Aitik are equipped with Aquila DM-5 drilling management system for precision

drilling through GPS positioning. MWD (Measure While Drilling) is a part of this system that

collects and archives the drilling parameters while drilling each hole. Although this data is not

fully used in production yet, it has been studied and evaluated several times and there is no

doubt in its usefulness.

Several parameters are included in MWD logs; some are independent parameters,

others depend on the geological and geotechnical properties of the rock mass. Depth, time,

rotation speed and feed force are independent parameters while penetration rate, torque,

vibration and air pressure are parameters that depend on rock mass characteristics. All these

parameters implement a systematic error in the measurements, but since there are no reference

measurements to evaluate the errors, one cannot quantify these errors in a numerical manner.

One of the most critical parameters in drill measurements is depth, due to the fact that

all other parameters are recorded along the depth of the hole. The depth of the hole also

decides start and end of drilling. In this project the depths of 215 holes right before and 1 hour

after charging were measured manually to control the MWD measurements of depth, the

results are presented in 4.2.2 and show an acceptably low error. However, a calibration of the

depth measuring system will improve the accuracy to a large extent.

Another issue with MWD data is its multi-dimensional nature. Each parameter is

recorded along the depth of the hole; in order to correlate a parameter to XY coordinates for

several holes, one should eliminate one of the dimensions. In other words, only one value can

be assigned to the hole in order to analyze the parameters horizontally. Usually penetration

rate (PR) is the governing parameter for analysis, which is also dependent on other drilling


parameters such as feed force. A solution to that is using a calculated index that includes

several variables. Specific energy (SE) is a concept that represents the work done per unit

excavated. The concept was introduced by Teale (1964) and has been evaluated by

Schunesson (2007). Teale (1964) introduced the following equation for specific energy:







SE = Specific Energy [N.cm/cm3]

F = Feed Force [N]

A = the cross-section area of the drill hole [cm2]

N = Rotation Speed [RPM]

T = Torque [Nm]

P = Penetration Rate [m/minute]

In this report both penetration rate and specific energy are presented. By introducing

specific energy alongside penetration rate, the errors in PR are eliminated or minimized; but

SE is still a parameter measured along the depth. In this study an average value within a fixed

depth of the hole has been considered as a median value for horizontal analyses. Figure 4.4

shows a sample MWD data for one of the holes. Custom VBA codes were written to analyze

the data; the average values have been calculated for the depth of the hole in between the two

red lines (the lines are unique for each hole). In this way the fractured part near the surface

(Sylta) as well as the low values at the bottom of the hole are ignored and errors due to

median calculation are eliminated and the median value can be considered as a suitable

representative of rock quality.



Figure 4. 4: MWD analysis of a sample hole (Hole #264).

The final issue with MWD data, for which no solution exists, is loss of data due to

mine network failure. As it will be shown in following chapters, MWD measurements were

not available for some parts of the bench. Fortunately the loss was not extreme, so there was

still enough data available to evaluate the test; but obviously more data is more favorable as it

helps to acquire more accurate results.

4.2.2 Charging

Although highly mechanized trucks are utilized for charging process in Aitik, errors still

occur due to rock fractures and human error. Manual measurements of the depth of 215 holes

before and after charging show high deviations resulted by operators’ error (Figure 4.5). The

measurements were conducted before and 1 hour after charging, the 1-hour delay was


sufficient for the expansion of emulsion explosive and it was short enough to avoid the

leakage of emulsion into joints and fractures.

Each point in Figure 4.5 represents the deviation of drilling and charging depths from

the planned depths of one blast hole, the closer the point to the 0 circle, the smaller the error.

Since the measurements were focused on a specific area on the bench, any comparison

between the errors of three sections would not be judicious.

Figure 4. 5: Drilling and charging errors of 215 blast holes.

Despite the problems caused by groundwater during and after drilling, figure 4.5

shows acceptably low errors in drilling depths. However, charging errors are distinctively

larger; a few holes were completely filled with emulsion, these overcharged holes were

blasted without stemming and caused fly-rock and air-blast risks. Some holes were similarly


undercharged; the undercharged holes result in low specific charge in some areas, which lead

to coarser fragmentation and more oversize boulders.

4.2.3 Shovel

Shovel logs are of great importance in evaluation of fragmentation and crusher performance.

The logging system records all the parameters every few seconds. The GPS positioning

system installed on the shovel records three different coordinates at each recording, one for

the shovel itself, one for the shovel bucket and the last for the digged area. The important

coordinates are digging and bucket coordinates; further analyses regarding fragmentation and

crusher throughput are correlated to the rock coordinates using digging coordinates. The

bucket position log is used to evaluate the digability of the fragmented rock; the bucket

coordinates are linked to the time taken to load the bucket, which is the standard measure of

the digability.

Depending on the GPS system and satellite visibility, there is an error of about 1 to 15

meters associated with GPS measurements, especially in higher latitudes (Aitik mine is

located at approximately 70 degrees latitude). By graphing the position of the shovel and

comparing it to the laser-scanned map of the bench it was revealed that the accuracy of the

GPS was more than expected. No overlap was observed near the walls and on the edge of the

bench, which shows a reasonably good accuracy.

4.2.4 Trucks (Minestar)

Aitik mine uses Cat® Minestar™ system for material tracking and real-time fleet management.

Logging the trucks activities is one of the capabilities of this system that is used in the current

study. Each truck is identified by a unique ID number, which is used to correlate the

fragmentation (extracted from manually taken photos) to the crusher parameters.


Unfortunately the system was functioning faulty and the truck IDs did not match the

ID signs on the trucks. Providentially the logs included correct data about times and locations

of trucks to extract a representative for each section of the bench. As a solution to faulty

logging of truck IDs, the truck cycle IDs from shovel are used; truck cycle ID is another

unique ID which identifies each cycle of the trucks within the mine. The procedure is

described in detail in 4.3.

4.2.5 Split-Desktop

An effective method to assess fragmentation is to acquire digital images of rock fragments

and to process these images using digital image processing techniques. In the case of post-

blast fragmentation, this is the only practical method to estimate fragmentation, since

screening is impractical on a large scale.

The Split-Desktop software was originally developed at the University of Arizona; in

1997 the technology was commercially available through a newly formed company, Split

Engineering. The Split software allows post-blast fragmentation to be determined on a regular

basis throughout a mine, by capturing images of fragmented rock in muckpiles, on haul trucks,

or from primary crusher feed. The resulting size distribution data can then be used to

accurately assess the fragmentation associated with different parts of a shot (Kemeny et al.


The basic steps involved in Split-Desktop analysis are acquiring images, pre-

processing the images to correct lighting, defining scales, delineating the images using Split

algorithms and finally correcting the delineation manually and defining fines (Figure 4.6).

The complete manual correction of delineations takes about 30 to 90 minutes per image,

depending on the quality of the image, lighting conditions and presence of dust, fog or other

obstacles and the level of precision in delineation. The software then applies statistical


algorithms to the 2D particle distribution to determine 3D particle volumes. To achieve an

average distribution multiple images should be processed, preferably with different scales.

Figure 4. 6: Delineation of a sample image with Split-Desktop.

Ouchterlony (2003), Kemeny et al. (2002) and Sanchidrian et al. (2006) have

extensive studies regarding the procedures and errors in measurements of fragmentation by

image analysis. Based on their studies and in accordance to the conditions, the sources of

errors associated with the current study can be concluded as follows:

- Sampling error

- Optical distortions

- Manual corrections of delineation


In order to minimize the sampling errors, efforts should be made to acquire evenly

distributed images among the bench area. The entire bench had been photographed during

loading, but unfortunately the limited data from Minestar did not permit an evenly distributed

analysis over the entire bench; as a solution to that three areas on the bench were selected as

representatives for three sections and images were sampled evenly within those areas.

The optical distortions were also mostly overcome by using a tele lens. The long focal

distance of the lens (300mm) minimized the image distortions to a great extent. The photos

were also taken from an approximately fixed angle and two separate scales were defined in

each image, so the scales and perspective of all images are roughly the same.

Split-Desktop results are highly user-dependent, in other words the fragmentation

obtained from an identical image is not the same for two different users. In that regard, only

one user has analyzed all images; the error of different delineating styles were also minimized

by making an efforts forth fairly identical delineation styles through all images. Although

much effort has been made in order to eliminate the errors in fragmentation analysis, the

existence of systematic errors in such process in undeniable.

4.2.6 FragMetrics

FragMetrics™ is a fragmentation measurement package provided by Motion Metrics

International Corporation. The package includes a camera installed on the boom of a shovel,

logging and storage devices, and a tablet PC with FragMetrics software to process the stored


The principle of FragMetrics is the same as Split-Desktop. However, the inert position

of the camera against the bucket eliminates the optical errors. In addition to that the

automated essence of the system provides a very useful tool for continuous monitoring of



FragMetrics is a newly developed system. It started operating from January 2012 in

Aitik, so very few experience regarding its results is available. Preliminary evaluations of the

results reveal that in contrary to its advantages to Split-Desktop, the very low resolution of the

camera leads to unreliable results. Figure 4.7 shows a sample image from FragMetrics camera,

the low resolution of the image limits the particles’ visibility down to boulders only.

Figure 4. 7: A sample image and delineation from Fragmetrics system.

A normal image analyzed in Split-Desktop has a resolution of around 2500x1500

pixels, showing a wide range of particles; but FragMetrics images are limited to 380x150

pixels, which is very low comparatively. Such resolution leads to faulty size distribution

analyses. Therefore the FragMetrics size distribution results were not used in evaluations and

discussions of this report; but as the boulders were clearly visible in the images, they

represented a very good source of data for oversize material. The images were used only to

determine the percentage of oversize material in each section of the bench.

4.2.7 Crusher

As mentioned before, the loading continues round the clock in Aitik and the loaded rock is

from different sources. In order to avoid rock assortment one of the crushers (KR 165) had


been only fed with the rock from the test bench. The mentioned crusher consists of two

primary gyratory crushing stations, so for every time point there are two energy consumption

values available. The energy consumption of the crushers are logged every 12 seconds.

The energy consumption of the crusher has a large scatter, so it is of great importance

to apply suitable statistical methods for sampling and analyzing the data. Figure 4.8 shows a

typical energy consumption diagram for one of the crusher lines. Each bar in figure 4.8

represents 12 seconds of crusher work and the values should be correlated to fragmentation of

the rock on trucks. Since the rock from a single truck takes approximately 5 minutes to be

crushed, a statistical analysis in necessary to come up with a median value for each truck.

Figure 4. 8: A sample of crusher energy consumption variations during 6 hours.

The mean values were calculated through VBA codes; the energy consumption of two

crushing lines were compared to pre-defined values to check if the crushers were in process or

idle mode; if either of them are in idle mode the other line’s energy consumption is assumed

real for that specific time point. For the time points that both crusher lines were in process, an

average of the two values are considered as true energy consumption. Over the time axis box

median values are calculated for periods of 5 minutes (similar to box-and-whisker diagrams).

It should be mentioned that the 5-minute period used in the calculations is an approximation


of the time between dumping and end of crushing, this value is obtained from observations at

the crusher and averaging the timespan.

4.3 Analysis strategy

With regard to data limitations mentioned in 4.2, a coherent approach to available data is

necessary for a consistent interrelation. Figure 4.9 shows the flow of the available sets of data

and the logical path to correlate them and bypass the data loss.

Figure 4. 9: Data-flow diagram used to correlate sets of analyzed data.

The main purpose of the diagram in figure 4.9 is to integrate all data sets into one

database of synchronized parameters. As seen, three sets of data come from the shovel; one is

the time interval of loading each bucket of the shovel, which provides a measure of digability;


second is the date and end time of loading a specific truck, which is used to designate the

affiliated photo for fragmentation analysis; and the third is the Cycle ID of the truck, this ID is

a substitute for the Truck ID, which is missing in Minestar. Truck cycle ID is then used to

extract the coordinates of the digged rock and end time of the truck cycle, which is equal to

dump time and is used to obtain the associated crusher efficiency from the crusher log.

MWD data is independent of the mentioned data sets; all available data is analyzed to

extract penetration rate and specific energy over the entire bench.

Dig coordinates for available truck cycles in Minestar, end time of loading from

shovel, and rock properties from MWD are then filtered using a VBA loop in a way that all

missing data are eliminated except the points for which all three sources have valid data.

The mentioned procedure provided a parametrically comparable set of data. Based on

this data, photos are selected and analyzed with Split-Desktop and Fragmetrics softwares. As

mentioned, Split-Desktop is used for a detailed fragmentation analysis and Fragmetrics is

only used for oversize material (boulder count).

To compare three sections of the bench, three representative areas are assumed. The

areas are selected based on the criteria of availability and validity of data, as well as

similarities in rock mass properties, which is described in 4.1.



5.1 Hardness of the rock (MWD)

Since the objectives of this study do not include detailed MWD analysis, only the most

important parameters are presented and discussed. As mentioned in 4.2.1, penetration rate and

specific energy are the governing parameters in MWD analysis (Mozaffari 2007). Figure 5.1

shows the penetration rate over the test bench and specific energy is plotted in figure 5.2; the

gray area in both plots represents the region with no available data. Although variation in

penetration rate is the simplest indicator of rock mass strength, it is influenced by several

factors. Since specific energy merges all factors into one single parameter, it can be used as a

substitute for penetration rate.

Figure 5.1 shows two main zones in the bench and few hotspots indicating harder

rock; the mentioned zones are significantly less differentiated in matter of specific energy

(Fig 5.2). However, a comparison between figures 5.1 and 5.2 shows very few distinctions

regarding the hotspots. These figures can be paired to the geology map of the bench (Fig 4.2).

Figure 4.2 shows dykes of Biotite and Amphibolite Gneiss in the bench, these dykes are

approximately located at the hard rock spots in figures 5.1 and 5.2; the higher strength of

Biotite and Gneiss also confirms this supposition.


Figure 5. 1: Penetration rate of drill bit.

Figure 5. 2: Specific energy consumed for drilling over the test bench.

These figures are mainly used as the basis for the selection of representative areas for

three sections of the bench. The areas are selected in parts of the bench with acceptably

similar rock mass hardness in a way that the hard rock spots are avoided as well as the areas

close to the border of the sections, which cannot be a fair representative of the whole section.


It should be mentioned that the missing data in MWD database along with the constraints

regarding Minestar data availability did not permit any better choice of areas (Fig 5.3).

Figure 5. 3: Representative areas for three sections with respect to limited MWD and Minestar data.

5.2 Swelling

The surface of the bench was laser-scanned right after the blast, the raw surface is shown in

Figure 5.4. For a better comparison the 2D-projection of this surface is shown in Figure 5.5,

which indicates the variation of swelling over the sections.


Figure 5. 4: 3D view of test bench's surface after the blast.

Figure 5. 5: Contour map of bench surface level after the blast.

q=1.02 kg/m3 q=1.17 kg/m3 q=0.91kg/m3


The significantly larger swelling of section A in figure 5.5 is compatible with

considerably higher specific charge of this section (1.17 kg/m3) compared to sections B (1.02

kg/m3) and C (0.91 kg/m3).

Although the specific charge in section B is larger than section C, no significant

alteration is observed in the amount of swelling for these two sections.

5.3 Digability

Timespan for filling each bucket by the shovel is plotted in figure 5.6 as a measure of

digability of the blasted rock. The gray area indicates the missing data.

Figure 5. 6: Digability of the blasted rock over the bench.

The highly scattered digging times in figure 5.6 do not lead to any meaningful

conclusion; no significant difference can be distinguished between the three sections of the



The high scatter can be due to variations in machinery and operators. As mentioned

before, two shovels have loaded the test bench, one of type P&H 4100C and the other of type

Bucyrus 495BII. In addition to that each operator works with a unique pace; the digging time

highly depends on the skills of the operator and the operation shift (day/night).

5.4 Fragmentation

Since boulders are the main problem in comminution process in Aitik, extra attention has

been paid to the oversized material. Oversized material is defined as particles larger than 100

cm, which is decided according to crushers’ opening size.

5.4.1 Split-Desktop

A total number of 78 photos were processed to evaluate the fragmentation of the test bench.

Respectively 23, 30 and 25 photos were analyzed for representative areas of sections A, B and


Complete size distribution diagram of three sections are presented in figure 5.7; the

curves are totally based on existing data and no curve fitting method is included. As seen in

the diagram, section B is of lowest uniformity and the most uniform curve belongs to section

A. However, sections B and C are approximately identical between X80 and X100.


Figure 5. 7: Particle size distribution of the fragmented rock.

For a better comparison the values of X50, X80 and percentage of oversize material are

presented in figures 5.8 and 5.9. Although section C has the largest X50 and X80 values, the

variations are minor between three sections.

Figure 5. 8: Size of the material at 50% and 80% passing.

33,26 28,64


62,94 69,6












Section A Section B Section C






X50 X80

q=1.17 kg/m3 q=1.02 kg/m3 q=0.91 kg/m3


Section A has the lowest X80; the deviation of X80 from reference bench is

approximately equal for sections A and C. Nevertheless, the percentages of oversize material

(Fig 5.9) show a notably higher deviation for section A. Section C includes the largest

percentage of oversize material, but the difference from the reference (section B) is less than

3%. However, section A includes 3.92% of oversize material, which is more than 7% lower

than reference section.

Figure 5. 9: Percentage of oversize material from Split-Desktop analysis.

Although this study mostly focuses on the coarse portion of particle size distribution

(X80 and oversize material), value of X50 is the most common measure of fragmentation;

therefore the values of X50 for three sections are plotted against their corresponding specific

charges on a log-log diagram in Figure 5.10. The line fitted to three points on the diagram

leads to the conclusion that section B does not follow the common trend of specific charge

and X50 correlation. The smaller X50 in section B, which shows finer material, could be due to

geological variations in three sections. As shown in the rock hardness diagram from MWD

analysis (Figures 5.1 and 5.2), section B consisted of slightly weaker rock compared to

sections A and C, such variation may have led to finer fragmentation and smaller X50. In













Section A Section B Section C

% O



Oversize material (Split-Desktop)

q=1.17 kg/m3 q=1.02 kg/m3 q=0.91 kg/m3


addition to that, the errors involved in drilling, charging and measurements of fragmentation

could have led to such results.

Figure 5. 10: Logarithmic diagram of X50 versus specific charge.

The graphs in figures 5.8, 5.9 and 5.10 compare the mean values of X50 and X80 for

the processed images; yet these mean values are extracted from highly scattered data sets. A

statistical analysis of the data resulted in the diagram presented in Figure 5.11, which

demonstrates the box and whisker diagram of X50 and X80 values for each section. The graph

presents the probability density of the data. Each box, marked with the first and third quartiles

and the median value in-between, shows the range that 50% of the points are set. As seen, the

boxes include a skewness factor and show the statistical dispersion of the data rather than the

normal distribution. Overlaps of the boxes, large interquartile range (IQR) of the mean values

and wide range of minimum and maximum values can be explained by the fact that X50 and

X80 values extracted from an image from a single truck cannot be a realistic representative of

the fragmentation. Since segregation of the broken rock is an inevitable phenomenon during

loading, each truck may carry more or less homogeneously distributed materials. In other

log q (kg/m3)





Section C

Section A

Section B


words, a single truck may include mostly fine materials while the next truck carries very large


Figure 5. 11: Statistical dispersion of X50 (left) and X80 (right) values.

In Figure 5.11, X50 values as low as 5 cm or as large as 105 cm exist for particle size

distribution of image analysis; similarly, X80 values vary in range of 25 cm to 145 cm. The

only way to draw a conclusion from such wide range, which is caused by segregation of the

materials, is to sample the images in a way that includes various ranges of material sizes on

trucks so the combination of several images leads to a more representative result. Therefore

one can deduce that in order to achieve realistic results, sufficient number of images should be

analyzed so the effect of segregation of the materials is eliminated.


5.4.2 FragMetrics

The size distribution curves produced by Fragmetrics software will not be taken into account

in discussions due to its nonsensical results. Four curves produced by Fragmetrics are

presented in Figure 5.12 and a sample report produced by the software can be found in

Appendix I. As seen in Figure 5.12, although the delineations were manually corrected, the

curves provide very little information regarding the uniformity and size distribution of the


Figure 5. 12: Four sample size distribution curves produced by Fragmetrics software.

Photos taken by Fragmetrics camera (on P&H 4100C shovel) are only analyzed as a

means to determine the percentage of boulders larger than 100cm. A total number of 195

images (65 images per representative area) were analyzed using Fragmetrics software.


Results of Fragmetrics analysis are presented in figure 5.13. According to the diagram,

section A includes the least percentage of oversized boulders followed by section C and B

respectively. Section A’s deviation from the reference is noticeably larger than section C’s.

Figure 5. 13: Percentage of oversize material from Fragmetrics Results.

A comparison of figures 5.13 and 5.9 reveals a large difference in percentage of

oversize material between Fragmetrics and Split-Desktop Analyses. The reason might be the

low quality of Fragmetrics images, leading to a faulty estimation of fine material. The

software cannot differentiate shadows from fine material, so all the shadows and voids in

between the particles are counted as fine material. Such error led to oversize percentages

lower than actual values.

5.5 Crusher efficiency

The correlation between coordinates of the rock and energy consumption of the crusher is

shown in figure 5.14. The energy value shown in the plot is a statistical median of energy

consumption of both lines of crusher 165; the parts for which the data was not available are

marked by gray color.


3,9 3,5







Section A Section B Section C

% O



Oversize Material (FragMetrics)


Figure 5. 14: Energy consumed to crush the rock (KWh).

According to the plot, section A had consumed the least amount of crusher energy.

The highest energy consumptions belong to an area at the border of sections B and C. A

meaningful correlation can be observed between figure 5.14 and MWD results (figures 5.1

and 5.2); the area close to MWD hotspots, which indicate harder rock, had consumed higher

crushing energies.



In order to deduce practical conclusions, an overall comparison of the results is required as

well as an estimation of economic efficiencies of alternatives. Table 5.1 summarizes the most

important results for each section of the bench. The drilling depth in calculation of specific

drilling is assumed equal to planned depth of 17.5 meters for all holes. Mean values are

calculated at 95% confidence of the data sets. The standard deviations (STDV) are also

mentioned to provide a measure of the data scatter.

Table 6.1: A summary of the test results.

Section A B C

Burden (m) 6 7 7

Spacing (m) 9 9 10

Height 15 15 15

Specific Drilling (m/m3) 0.0216 0.0185 0.0167

Specific Charge (kg/m3) 1.17 1.02 0.91

Swelling (m)

Mean value 7.3 4.8 4.4

STDV 1.25 1.33 0.71

X50 (cm)

Mean value 33 28 41

STDV 12.2 15.6 14.6

X80 (cm)

Mean value 63 70 80

STDV 10.2 11.0 15.3

Percent Oversize (%)

Mean value 4 12 14

STDV 0.86 1.92 1.81

Crusher Energy Consumption (KWh)

Mean value 280 380 390

STDV 62.7 70.3 66.5

As section B is the currently used design in Aitik mine, it is assumed as the reference

to compare two other sections; in order to make an unbiased comparison between the factors

mentioned in Table 6.1, percentages of deviation from reference is plotted in Figure 6.1.


Figure 6. 15: Percent deviation from reference section.

Specific Drilling and specific charge are the main measures of cost estimation. As

seen in Figure 6.1, section A had about 15% higher cost of drilling and charging compared to

section B. Same costs are -10% for section C, indicating a large thrift in total cost.

High specific charge of section A resulted in 50% more swelling compared to

reference section. However, section C had only 8% less swelling than section B.

The deviation of X80 in sections A and C are +14 and -10% respectively, which is

fairly uniform. But the percentage of oversize material shows very different deviations;

section A included 60% less boulders compared to section B; but section C included only

16% more oversize material.

Crusher energy consumption is also differently deviated for sections A and C; the

crushing of the rock from section A consumed 25% less energy than the rock from section B.

Percent deviation from reference section


In contrary, energy consumption of the crusher was only 2% higher than the reference for

section C. In other words, sections B and C consumed fairly equal amounts of energy in the

crusher. Comparing MWD analysis results to crusher energy consumption plot (Figure 5.14)

reveals a meaningful correlation between crusher efficiency and hardness of the rock; the

hotspots of MWD plot, indicating harder rock, consumed significantly larger amounts of

crushing energy. To summarize, the following conclusions can be drawn from the results:

- Section A, with a 6x9 m drilling pattern and 1.17 kg/m3 of specific charge, provides a

smaller X80 and lower percentage of oversize material; it also reduces the energy

consumption of the crusher by around 25%. However, X50 shows a 13% increase

compared to reference section. The costs of drilling and charging also increase by 15%.

- Section C, with 7x10 m drilling pattern and 0.91 kg/m3 specific charge, produced

coarser fragmentation and more boulders; in addition to that, visual observations

confirmed that the size of the boulders were significantly larger than the reference.X50

and X80 show 14% and 41% increases respectively. The percentage of oversize

materials also increased by 17%. The fragmented rock consumed only 3% more

crushing energy compared to the reference section, which is almost equal to reference

section energy consumption. Furthermore, the drilling and charging costs of section C

were 10% lower than the reference costs.



Two drilling patterns have been tested, evaluated and compared to the currently used pattern;

the test results are in accord with the theoretical correlations of specific charge and


In order to put the results into practice, comprehensive economic analyses as well as

another comparative test seem necessary. If the post-blast benefits of 1.17 kg/m3 of specific

charge in 6x9 m drill pattern overcome the additional costs of extra drilling and charging, a

confirmative test should approve the results prior to application of the new drilling pattern.

Since the deviations from reference are relatively low for section C (Fig. 6.1), the

7x10 m pattern and 0.91 kg/m3 of specific charge can still be considered as an alternative

option. The increase in X80 and oversize materials are about 15%, but the energy consumption

of the crusher does not increase significantly and the pattern saves 10% of drilling and

charging expenses.

The study suggests advantageous practices of MWD database to predict spots of hard

rock and low crusher efficiency. This data can be used to modify the drill and blast design of

benches to reach uniform fragmentation throughout the whole area. The meaningful

correlation between hard rock indicators on MWD maps and significantly larger crushing

energies can also be used to eliminate the effect of geological uncertainties in future tests


Minestar system is another potential for improvements; a well-functioning logging

system opens the way for continuous surveys of mining process. Minestar logs act as a link

between different sections of the mine, so in order to improve the overall efficiency of the

mine it is critical for Minestar system to fully function.

Fragmetrics system is also an advantageous means for continuous monitoring of

fragmentation. However, low image quality and faulty analysis algorithms do not let this


system to be used in full capacity. A high resolution camera equipped with an anti-vibration

system, together with more advanced image processing software, can provide more realistic

results in regard of continuous fragmentation measurements. Finally, following operations are

suggested for future:

- A financial analysis of tested patterns; a confirmation test should be defined if either of

them leads to higher benefits.

- Efforts to improve the function of Minestar and mine network in order to collect as

much data as possible.

- Efforts to improve the function of Fragmetrics system as a key in fragmentation




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APPENDIX I: Fragmentation analysis of FragMetrics software.

Region: S1_210_13 Shovel: 1152 Number of bucket images processed: 462 Date range: May 9, 2012 12:22:16 AM GMT+2:00 ~ May 20, 2012 5:31:56 AM GMT+2:00 Duration: 11 days 5 hours 9 minutes Calibration bucket width: 460 cm Report date: May 20, 2012 1:31:26 PM GMT+2:00 History view of P10 to P100

History view of P50, P80, and P100

ii Cumulative Rock Fragmentation Graph

Table 1 Passing Percentage Numbers (unit: cm)

P10 P20 P30 P40 P50 P60 P70 P80 P90 P100 fine 0.4 0.9 1.2 1.5 1.8 5.1 9.3 12.4 333

Schumann distribution modulus = 1.119 Schumann size modulus = 2.8 cm Table 2 Fragmentation Target Parameters

Oversize 100 cm Undersize 5 cm

Table 3 Fragmentation Results

Percent Oversize 3.1 % Percent in Range 27.1% Percent Undersize 69.8%

Generated by: Fragmetrics™ - Tablet

iii APPENDIX II: An introduction to Air-decking in Aitik.

i. Introduction

The utilization of air-decks in production blasting is a fairly new method in mining

industry, although the concept has been studied and practiced since 1986. Melnikov was the

first to introduce air gaps inside the blast hole and most of the early research on this topic has

been conducted in the former Soviet Union (Lu and Hustrulid 2010).

The main concept of air-decking consists of decreasing the amount of explosive and

improving the blast-induced fragmentation by means of introducing air gaps in the explosive

column. Theoretical studies and field experiments by Melnikov and Marchenko(1971),

Chiappetta and Mammele(1987), Bussey and Borg(1995) and Jhanwar et al. (1999) show a

decrease in mean fragment size, an increase in the uniformity of fragmentation, and also a

decrease in explosive consumption by 10-30%. Laboratory experiments carried out by

Fourney et al. (1981) regarding air decking in thick plexiglass blocks revealed that air

decking increases the effect of shockwave on the material by a factor of 2 to 5. Lu and

Hustrulid (2003) reviewed the theory of airdecking and provided guidelines regarding the

application of this method.

In spite of these studies, the mechanism of airdecking has still not been fully

understood and utilization of this method does not always improve blasting results.

ii. Theory

Air-decking technique comprises the use of one or several air gaps in the explosive

column in order to optimize the fragmentation and reduce the explosive consumption. The

theory proposed by Melnikov and Marchenko (1971) hypothesizes that the air gap is a means

of shockwave reflection within the borehole. The air-deck acts similar to a cushion and

produces a series of aftershocks that extend the network of microfractures in the rock. The

aftershocks are produced by three main pressure fronts: shock front, pressure front due to

iv formation of explosion products behind the detonation front and reflected waves from the end

of explosive column. Although the air-deck causes a reduction in borehole pressure, the

repeated loading of the rock by a series of aftershocks prolongs the action time of the

shockwave and results in improved breakage (Jhanwar et. al 1999).

A series of tests by Fourney et al. (1981) in Plexiglass models supported Melnikov’s

theory. It was observed that the shockwave reflects back from the base of the stemming

column and reinforces the stress field. This process is repeated several times; therefor the

duration of the shockwave action is increased by a factor of 2-5. This mechanism leads to a

larger volume of radially fractured material rather than heavy breakage in the area adjacent to

the charge column, see Figure I.1.

Figure I. 1: Development of crack network in Plexiglass under the influence of an air-decked explosive column (after Fourney et al. 1981).

iii. Design

Despite the confirmative results from field and lab tests, some important technical

problems are still unsolved. The location of the air deck in the blast hole and the length of the

air column are two of the main questions to which there are different answers proposed.

Moxon et al. (1993) showed that as the length of the air-deck is increased the fragmentation

v becomes finer relative to that of a full-column charge. The reduction however is relatively

small until a critical length is exceeded. The critical length depends on the strength and

structure of the rock mass. From the model tests, a critical air-deck length of 30–35% of the

original explosive column was determined. They concluded that a mid-column air-deck has a

larger effect on fragmentation than that of the top or bottom air-deck. Liu and Katsabanis

(1996) and Katsabanis (2001) found that there exists a minimum air deck length for the

technique to be beneficial; they also found that variations to the top air deck, such as bottom

and mid-column air decks do not make significant improvements in production blasting.

Recent investigations by Hustrulid et al. (2003) also show that in case of top air decks, there

is a minimum limit for the air-deck length to be effective on the fragmentation. The length of

the air-deck is the most important parameter, so this limit has been determined empirically by

several tests and it is presented as the “Air-decking ratio”, which is the ratio between the

length of the air deck and the total length of the explosive column:


aa LL


= (I.1)

where Ra is the air-decking ratio, La is the length of the air-deck and Le is the length of the

explosive in the column. The corresponding value for R, according to Hustrulid et. al (2003),


374.0164.0 ≤≤ R (I.2)

For the current case in Aitik, the practical constraints do not allow a ratio as high as

0.3, so the following designs are suggested based on practical applicability of them in Aitik.

As seen in Figure I.2, a total length of 18m has been assumed for the boreholes. The

length of the air-deck is suggested in accordance to rules of thumb and applicability in the

site. The length of the deck is at minimum 2.5 meters that includes a safety margin for some

immerging of the barrier into the emulsion.


Air-decking ratio and amounts of reduction in explosive are mentioned in table 1 to

provide a comparison between the options. The price of emulsion explosive and the diameter

of the borehole are assumed 5 SEK/litre and 318mm respectively4.

Figure I. 2: Suggestions for air-decking in Aitik; a)original design, b)2.5m air-deck, no charge reduction, c) 3m air-deck, reduced charge, d) 2.5m air-deck, reduced charge.

Tabe I. 1: A comparison of the designs and cost reductions per hole.

Type Charge column (m)

Air column (m)

Stemming (m)

Air-decking ratio

Charge reduction


Cost reduction

(SEK) a (original) 12.5 0 5.5 0.00 0 0.0

b 12.5 2.5 3 0.17 0 0.0 c 11 3 4 0.21 120.6 603.2 d 11.5 2.5 4 0.18 80.4 402.1

Since an extra cost will be added for the air-decking instrumentation, the c and d

designs are favorable, because of their lower explosive cost. Between c and d, the latter has

also the advantage of smaller reduction in amount of charge and an acceptable stemming


4 The price is a rough fictitious assumption.

vii iv. Implementation of air-deck

The air gap in the blast hole is most commonly implemented through usage of

balloons or gasbags. The gasbag or balloon is lowered to the desired depth in the blast hole

and inflated; upon inflation, the air pressure inside the balloon fixes it inside the hole and

depending on the location of the air-deck, stemming or explosive is filled on top of the


Different types of gasbags and balloons are available on the market, which can be

categorized into two main groups: Chemically inflated and mechanically inflated. Chemical

gasbags are inflated by means of chemical reactions of the material inside the bag; the

reaction is either between two substances that are mixed when a button is pressed, or by a

pressurized gas capsule. These gasbags are easy to implement and fairly cheap; they also take

short time to install in production holes. Mechanically inflated gasbags are more like regular

balloons modified to withstand high pressure of blast hole. These balloons are inflated

through an air compressor, which can be easily installed on any truck. These balloons take

comparatively shorter time for installation (10-20 seconds) and usually have a smaller chance

of failure. The installation method for each group varies depending on the gasbags’ type and

manufacture, see Figure I.3.


Figure I. 3: Left: Samples of commercially available balloons (Left) and gasbags (Right).

v. Air-decking and Aitik conditions

Aitik mine is located in northern Sweden with long and harsh winters; the temperature

in the winter can reach -40°C. The extremely low temperatures can cause malfunctions in

chemical gasbags or pressurized balloons. In addition to that, high level of groundwater

causes the blast holes become filled with water almost instantaneously after drilling; lowering

an inflating gasbag 3-4 meters deep into a water-filled hole is not a fast and easy task for

production blasting. Previous tests of capsule-inflated gasbags were not successful due to low

air pressure in cold weather; the technicians also faced difficulties in implementation process

of the gasbags in the water-filled blast holes.

Gasbags and balloons are usually lowered into the desired depth by a rope. In case of

Aitik mine, a long piece of wood is used to force the bag into the water-filled holes. In a

future tryout a modified type of capsule-inflated gasbags are going to be tested; the capsules

are expected to function normally in cold weather, but the mechanism of inflation will still be

problematic in water-filled areas of the mine. These gasbags have a diameter less than the

ix desired one; the capsule inside the gasbag should be triggered on surface and only 20-30

seconds after triggering the gasbag will pop to the desired diameter. For the case of water-

filled holes, it might be challenging to lower a half-inflated gasbag into the blast hole during

such short interval.

Mechanically inflated balloons appear to be a better choice than gasbags. They are

usually lowered into the hole by a hose, which is designed to come off when the balloon is

inflated. The balloons are lowered in deflated estate, so the technician will face less difficulty

in lowering the balloon into the water-filled holes. The balloon is then inflated by means of

an air compressor on the truck, so the inflation process takes less time than capsule-inflated

gasbags and the technician should only hold the balloon in place for a few seconds until it is

fixed in the hole.

It should also be mentioned that the material used in manufacture of balloons are

supposed to be more suitable for high air-pressure and heavy load of stemming on top of the

balloon. Some stereotypes of capsule-inflated gasbags were tested on the surface and there

were cases of rupture by air pressure.

vi. Conclusion and recommendations

Although the mechanism has not been fully understood, air-decking is a useful

technique to improve the upper portion of fragmentation in production blasting. The field

tests and successful cases of application in other mines support the theory behind it. But air-

decking is not beneficial for all mines. In case of Aitik mine, the first question is whether this

technique can make an improvement in fragmentation or not. Secondly, the technique should

be adapted to the harsh conditions in Aitik, which had led to unsuccessful tryouts earlier.

Between two main types of commercially available air-decking gears, the balloons

appear to fulfill more requirements than capsule-inflated gasbags, but it is recommended to

test both types and observe the results. The tests should include both cold weather and water-

x filled holes conditions. It is also recommended to test them as a simulated production blast i.e.

long time stay in the hole before the blast, etc.

Depending on the results of the tests, a full-scale blast can be air-decked and blasted.

Careful monitoring of the fragmentation and comparing it to normally blasted benches may

reveal whether the technique will be beneficial in Aitik or not.


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