advanced open pit planning and design 2014(for nicico)finaldraft

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ADVANCED OPEN PIT MINE

PLANNING AND DESIGN

Presenter

Prof Emmanuel Chanda

The University of Adelaide, Australia

ADVANCED OPEN PIT MINE

PLANNING AND DESIGN

M1-Strategic mine planning M2-Open pit optimisation M3-Mine Production scheduling M4-Optimum Cut-off Grades M5-Mine Planning Software M6-Mine-to-Mill Optimisation M7-Equipment Selection M8-Financial Technical Modelling M9-Dewatering and Pumping

Open Pit Mine Planning and Design 2

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Objectives

Fundamentals of open pit mine design and current developments in planning and design methodology,

Current industry practices to maximise economic return.

Open pit mine planning and design process in theory and practice,

Unit Operations Drill-Blast-Load-Haul Apply this knowledge to plan/evaluate new

open pit projects and/or existing mines.


What do you expect to learn from this

Course?


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Module 1

Strategic Mine Planning


1. What is strategic planning?

2. Mine planning process

3. Mining strategy

4. Feasibility Studies

5. Exercises

Big picture mine planning and design process

Big picture decision-making process

Applies to Greenfields as well operating mines

SP takes place at all levels of the company Corporate level: vision, mission, feasibility, etc Business unit level: expansion of production Mine level: medium/long term production strategy

Analogy: military strategy

Overview/scope


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What is Strategic Mine

Planning?

Strategic mine planning is concerned with those

decisions that largely determine the value of the

mining business whereas tactical mine planning

deals with the tasks required to actually achieve

that value.

Both types of planning are necessary; they can be

looked at separately, even discussed separately,

but they cannot be separated in practice!


Prospecting Exploration Closure

Life cycle of an orebody

Min

e P

lan

nin

g

Strategic Mine

Planning

Development Production

Types of planning and mine life cycle

Tactical Mine

Planning


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Strategic mine planning focuses on those technical variables that affect the life of a mine and the value of the underneath mineral resource

It starts with the discovery of the mineral resource and finishes when it is exhausted or abandoned.

Go! List variables (factors) considered in SMP


Business Strategy

Strategic

Planning

Economic

Evaluation

Decision-

Making

Behaviour

Mine Planning


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Decision-Making Behaviour:

Risk Averse seeks other business goals

Risk Neutral seeks maximise NPV


12

Mine Planning Process Flowchart

Open Pit Mine Planning and Design

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Mine Planning Process

Four main stages of mine planning process:

Geology of resource

Value of resource

Long-Term planning (Strategic) feasibility

studies

Medium-term/Short-term planning - production

Mine Planning Process*:

Geology + Data Analysis Resource Model

Optimisation

Mining Method Selection

Mine Design Financial Technical Model Optimal Schedulling

* A dynamic and iterative process * Open Pit Mine Planning and Design 13

Activity 1: Work in Groups of 2-4

To plan a new open pit mine in Kerman Province. List all the

data required to perform a feasibility study and where these data would come from.


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Technical Aspects:

Once the geological features are understood and the physical characteristics of the ore body are determined, the main technical decisions that follow are:

Mining method selection

Processing route

Scale of operation (size)

Mining sequence

Selective cut-offs (e.g. cut-off grade at the mine)


All these variables are inextricably interrelated in the sense that they cannot be determined in isolation from each other

Moreover, they cannot be determined without taking into account the market variables and related data from the geologic, metallurgical, geotechnical, and environmental models.

.as shown on next slide


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MARKET

Metallurgical

Model

Geotechnical

Model Environmental

Model

Geological

Model

Mining

Method

Scale of

Operation Mining

Sequence

Selective

Cut-offs

Processing

Route

MINE PLAN


Mining Method Selection

The choice of the mining method depends on the

shape, emplacement and properties of the

orebody and host rock; again, beyond technical

considerations, this is an economic decision

In general, there are two main mining methods:

Surface mining (open pit, quarries)

Underground mining (block caving, cut & fill)


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However, depending on the emplacement of the orebody and its grade distribution, there are cases where both methods are feasible e.g. open-pit followed by underground mining or the other way around

This is the classic case of sub-vertical deposits such as kimberlitic pipes containing diamonds and some porphyry copper deposits


Many decisions concerning the choice of the mining method are related to the "opportunity cost concept

For example:

In massive, disseminated deposits that are close to surface, open pit mining is more productive than an underground

Underground mining usually requires more development and preparation works

Economic considerations


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Considerations in Mining Method Selection Finances:

Finance influences method selection: Length of pre-production development and phases

Thoroughness of the ore body delineation program

Scale of operations bulk mining methods, eg., block

caving

Technology applications - automation


Markets

The mining method should be flexible enough to respond to market changes. When and how to high grade during peak commodity prices Changes to mine development schedule Focus on production of by-products (eg. cobalt in copper ore) Mining companies are price takers. What can be done about this?


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Technology and Human Resources

Choice of particular mining method commits operation to certain type of technology, equipment, human resources and processes. Later change in method will be at a cost Must allow for possibility of introducing new technology Necessary skills must be available to operate selected mining system Lack of expertise may eliminate a particular mining method, though technically suitable. Consider specific training and supervision


Processing route

The selection of the processing route depends

essentially on the characteristics of the ore; however,

beyond technical considerations, this is a business

decision

Essentially, there are basically two main routes:

Physical methods (concentration)

Chemical methods (hydrometallurgy)


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Acceptable

Mineral

Comminution Liberation

Unacceptable

Classification

Separation Concentration

Physical Chemical


Factors to consider

Products recovered

Recoveries and achievable grades

Environmental aspects

Market considerations

Capital and operating costs

Cycle times

Mine plan

Cash flow and profitability

In short, technical and financial considerations


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Lab testing for initial investigation

Core samples and samples from outcrops

(chip samples) Pilot tests to confirm lab tests and design

Core samples and some bulk samples from

underground workings Industrial tests to feasibility

Bulk samples from underground workings

and additional core samples

Metallurgical tests


Scale of the operation

The scale of the operation refers to production capacity, which in turn is related to the physical size of the installations at the mine and plants

This is directly related to the capital investment required to produce the final output deemed to put in the market

The larger the scale, the higher the investment and production


Case Study: Olympic Dam Expansion Project

in South Australia

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From the point of view of a mining project, the scale of the operation is the dominant factor for establishing the mine life and business value

There is a compromise between the NPV of a project and its size the optimum size exits, because a very large operation may shorten the mine life too much, making the marginal investment unworthy


Scenario 500 kt/d

Scenario 150 kt/d

Scenario 72 kt/d

Scenario 300 kt/d NPV

(MUS$)

Scale of operation

1000

2000

2700

3000

Size-profitability-risk relationship

Risk


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Mining Sequence and Final Limits

It refers to the path or trajectory employed to exploit a mine from an initial situation until reaching the final limits or exhausting the ore reserves

Usually, these two variables are treated separately but because of their co-dependency they should be handled together


The mining sequence is usually defined in terms of sequential cuts or "sectors in which a final mining envelope is split to guide the mining extraction

These sectors can be phases, cut-backs or push-backs as they are usually called in open-pit mining; or blocks, panels, rooms or stopes as these are commonly referred to in underground mining


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It is worth noting that the partition of a final

mining envelope into cuts or sectors is done

because the time value of money

In effect, the purpose is to postpone

expenditures and bring forward revenue as

much as possible from production sales


To illustrate how the time value of money

affects the economics of mining it is useful to

introduce the saw graph tool

It assumes that mining activities always

require some preparation works

(development) prior to ore extraction:

Stripping in open pit mining (t, m3)

Developments in underground (m3,

m2, m, t)

The scheduling saw graph


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The scheduling Saw Graph

Time yr-1 yr-2 yr-3 yr-4 yr-5 yr-6

Minimum Ore Exposure


Integral optimisation of the final pit

1

2

3

4

5

6

100 t (waste)

500 t (ore)

Revenue 2.2 $/t

Cost -1.0 $/t

Exploitation phases


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Partial and cumulative tonnage

Ore Waste O/W Ratio Ore Waste O/W Ratio

1 500 100 0.2 500 100 0.2

2 500 300 0.6 1,000 400 0.4

3 500 500 1.0 1,500 900 0.6

4 500 700 1.4 2,000 1,600 0.8

5 500 900 1.8 2,500 2,500 1.0

6 500 1,100 2.2 3,000 3,600 1.2

7 500 1,300 2.6 3,500 4,900 1.4

Partial tonnage Cumulative tonnagePhase

Breakeven point Phase 6


When neither the time value of money nor other

operational factors such as mine and plant

capacities are taken into account, the optimal final

limit is reached at Phase 6

The implicit assumption is that ore is exposed

simultaneously with waste and that ore revenue

occurs at the same time as waste cost


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When accepting that ore and waste extraction have to consider certain physical restrictions in their programming (phase size and available equipment), then the time value of money becomes a relevant issue

The programming can be done using the saw graph early described


Case 1: Open pit plan with 6 phases

yr-1 yr-2 yr-3 yr-4 yr-5 yr-6

Plant 500 t/y

Mine 1,300 t/y

500

500

1,000

1 2

3

4 5

5

4

2

1

3 6

6

Time

Waste removal


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Economic evaluation: Phase 6


1,000

- 1,000

+1,250

0

- 800

- 300

-225 -546 +706

Present value(t=0, r=10%) = - 65




1,000

- 1,000

+1,250

0

- 500 - 400

-331 -376 +776

Present value(t=0, r=10%) = + 70


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Case 2: Open pit plan with 5 Phases

yr-1 yr-2 yr-3 yr-4 yr-5

Plant 500 t/y

Mine 1,300 t/y

500

500

1,000

1 2

3

4 5

5

4

2

1

3

Time




1,000

- 1,000

+1,250

0

- 800

- 100

-83 -601 +776

Present value (t=0, r=10%) = + 92


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Economic evaluation

Partial Cum Partial Cum

1 1,036 1,036 1,036 1,036

2 733 1,769 733 1,769

3 485 2,254 485 2,254

4 250 2,504 275 2,529

5 70 2,574 92 2,621

6 -65 2,509 - -

Phase

Net Present Value @ r = 10 % ($)

Case 1 (6 Phases) Case 2 (5 Phases)


Summary of results

1

2

3

4

5

6

Breakeven final

limit (Phase 6)

Discounted final

limit (Phase 5)


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Considering an underground

alternative

1

2

3

4

5

6


2 open pit phases, 4 underground lifts

3

4

5

6

NPV(1)

$ 800

(1) Net present value at the beginning of year 1

1

2


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3 open pit phases, 3 underground lifts.

3

4

5

6

NPV(1)

$ 450

$ 200

$ 50

(1) Net present value at the beginning of year 1

1

2


NPV of underground lifts

Lifts

500

+800

0

+450

NPV Lift 3 (t=0, r=10%) = + 350

+200

+50

3 6 4 6 5 6 6

NPV Lift 4 (t=0, r=10%) = + 250

NPV Lift 5 (t=0, r=10%) = + 150

NPV Lift 6 (t=0, r=10%) = + 50


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Economic evaluation

(Open Pit vs Underground)

Partial Cum Partial Cum

1 1,036 1,036 1,036 1,036

2 733 1,769 733 1,769

3 485 2,254 485 2,254

4 275 2,529 275 2,529

5 92 2,621 150 2,679

6 50 2,671 50 2,729

Phase

Net Presente Value @ r = 10 % ($)

Case 3 (OP/UG) Case 4 (Optimum)


Optimum configuration

3

4

5

6

1

2


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Summary of evaluations

1 1,036 1,036 1,036 1,036

2 1,769 1,769 1,769 1,769

3 2,254 2,254 2,254 2,254

4 2,504 2,529 2,529 2,529

5 2,574 2,621 2,621 2,679

6 2,509 - 2,671 2,729

Net Present Value @ r = 10 % ($)Phase

Case 1 Case 2 Case 3 Case 4


NPV and Shareholder Value

Net present value ($) 2,509 2,621 2,671 2,729

Firm's net debt ($) 1,000 1,000 1,000 1,000

Firm's market value ($) 1,509 1,621 1,671 1,729

N Shares 1,500 1,500 1,500 1,500

Share value ($/Sh) 1.01 1.08 1.11 1.15

Case 1 Case 2 Case 3 Case 4Firm's Information


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Role Of Feasibility Studies

Why Feasibility Study

Scoping Study

Preliminary Study

Bankable Feasibility Study

Risks


Origin of the FS The Feasibility Study is a development of mine

valuation reports. These had remained almost invariable from 1900 to 1960s.

More complex and larger mining operations in 1960s and 1970s required sophisticated studies and reporting. The FS was developed which:

Brings together all aspects of an operation into one study

Looks at the inter-relationships and tries to solve any problems

Aims to determine technical and economic viability of a project


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Feasibility Studies

Demonstrate that the project is economically

viable to the satisfaction of the Board, the

shareholders and all other stakeholders.

The FS enable the financing of:

Preliminary earthworks

Engineering construction

Infrastructure


Provide a detailed analysis of all the

factors affecting a projects viability.

Enable determination of a go or no go decision

Have become an aid in obtaining

financial backing

Feasibility Studies


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Phases

Scoping Study

Pre-Feasibility Study

Final Feasibility Study


Scoping Study The Scoping Study is a preliminary investigation into a

project between a back of envelope and a pre-feasibility study, or an assessment of necessary size, grade of a target to explore.

It may also be called a Concept(ual) Study.

The study is normally undertaken with limited technical and other data being available.

There is high reliance on experience and knowledge of similar projects and it normally involves a basic level of literature search.


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Aim of A Scoping Study

Provide a document for decision-making.

Identify key factors that will influence the

overall outcome of the project.

Identify and briefly assess possible options,

identify risks

Give an indication of the potential financial

worth of the project

MCA Project Management in Mine Planning and Design


Outcomes of Scoping Study The outcomes will depend on the situation of the

particular project and reasons for the study. The

outcomes of a scoping study mayl include:

Information for decisions regarding the future of

the project.

Identification of key factors and probably risk

areas, requiring further early investigation.

Highlighting project activities or aspects which

have the greatest influence (sensitivity) on the

project value or return.

Highlighting project parameters that require

more accurate measurement or definition.

A proposed plan to advance, or close, the project

with schedules and estimated costs. Open Pit Mine Planning and Design 63

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Open Pit Mine Planning and

Design

A scoping study for the Flying Fox T1 deposit as a stand-alone underground mine with offsite ore treatment was prepared by mining consultants Golder Associates Pty Ltd.

Main outcomes of the T1 scoping study were as follows: Mineable Resources at 196,000t @ 5.4% Ni*

Contained nickel in concentrate 10,587 Ni tonnes

Gross Revenue (after royalties) A$101 million

Operating costs (mining, site, transport, treatment) A$201/tonne ore (A$1.70/lb Ni produced)

Capital costs - Establishment A$6.0 million

- Mine development A$12.8 million

Undiscounted Net cash flow (before tax and D&A) A$37.2 million

* Note : Mineable Resources do not constitute a JORC compliant

resource or reserve category.

Scoping Study- Case Study

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Preliminary Feasibility Study

Decisions: Abandon project, change or continue?

Planning: Focus continued investigations on project-critical areas.

Justify detailed site investigation and resource definition.

Determine the optimum project scope.

Identify risks opportunities and potential show stoppers/fatal flaws.

Economic justification: Justify a full feasibility study.

Help sell the project.

Obtain private finance.

Development: Support permitting and stakeholder liaison



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Design

Pre Feasibility looking at

alternate scenarios Andean Golds Cerro Negro project in Argentina

Open pit optimization for the Vein Zone was completed using Whittle 4x software and recovered gold block grades. A US$800/oz gold price was used as the base case and the remaining inputs are as shown below:

Pit Optimization Parameters

Bench Angle 85o

Berm Width 9 metres every 20 metres

Pit Slope 52o overall slope with ramps

Mining Cost $1.50 per tonne mined

Processing Cost $14.00 per tonne ore

General & Administrative Cost $3.00

per tonne ore

Pit

Revenue

Factor

Waste

Tonnes

('000)

Ore

Tonnes

('000)

Recovered

Au (g/t)

Recovered

Ounces

('000)

Strip Ratio

(W:O)

1 0.30 9,763.1 2,083.3 5.30 355.0 4.69

5 0.38 11,922.4 2,580.3 4.84 401.3 4.62

10 0.48 14,631.9 3,111.4 4.43 443.6 4.70

15 0.58 15,704.0 3,580.2 4.06 467.2 4.39

20 0.68 16,357.2 3,941.0 3.81 482.6 4.15

25 0.78 16,697.4 4,143.1 3.68 489.8 4.03

28 0.84 16,765.5 4,247.6 3.61 493.0 3.95

29 0.86 25,403.2 4,547.3 3.56 520.4 5.59

30 0.88 25,370.3 4,581.3 3.54 521.2 5.54

36 1.00 25,725.8 4,750.5 3.45 526.2 5.42

40 1.14 26,977.6 5,016.1 3.31 534.3 5.38

45 1.28 27,120.3 5,110.1 3.26 536.3 5.31

50 1.42 27,163.4 5,199.4 3.22 537.9 5.22

55 1.60 29,865.5 5,363.9 3.15 543.6 5.57

60 1.72 29,983.6 5,422.6 3.12 544.6 5.53

67 2.00 30,555.8 5,536.6 3.07 546.5 5.52

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Design

Pre Feasibility scheduling

production

Period

Oxide

"Ore"

(000's

Tonnes)

Oxide "Ore"

(g/t Au)

Mix "Ore"

(000's

Tonnes)

Mix "Ore"

(g/t Au)

Totals

(000's

Tonnes)

Totals

(g/t Au)

Waste

(000's

Tonnes)

Strip

Ratio

Pre-production 2.4 2.58 2,290.7

Year 1 644.1 3.05 28.2 4.00 672.3 3.09 3,615.3 5.38

Year 2 670.6 3.71 4.7 2.18 675.3 3.7 5,063.0 7.50

Year 3 643.1 4.62 31.7 3.65 674.9 4.58 2,022.2 3.00

Year 4 758.0 4.39 89.3 3.45 847.3 4.29 7,476.7 8.82

Year 5 1,186.7 2.55 163.3 2.76 1,350.0 2.58 7,619.7 5.64

Year 6 279.6 4.39 130.4 2.52 410.0 3.8 2,287.7 5.58

Totals 4182.1 3.59 447.7 2.96 4,629.8 3.53 30,375.3 6.56

Portable Ore Portable Ore Portable Ore

000's Tonnes 000's Tonnes 000's Tonnes

Year 1 672.3 3.09 677.7 11.54 242.81 1,350.0 7.33 121.89

Year 2 675.3 3.70 674.7 14.07 258.86 1,350.0 8.88 129.37

Year 3 674.9 4.58 675.1 12.97 203.05 1,350.0 8.77 101.55

Year 4 847.3 4.29 502.7 6.69 120.41 1,350.0 5.18 44.84

Year 5 1,350.0 2.58 1,350.0 2.58 0.00

Year 6 410.0 3.80 410.0 3.80 0.00

Totals 4,629.8 3.53 2,530.2 11.63 212.16 7,160.0 6.39 74.97

Cerro Negro Total

g/t Au g/t Ag g/t Au g/t Agg/t Au

Period

Vein Zone Eureka

Open pit schedule

Open pit and underground schedule

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Design

Pre Feasibility things will change

over time Brisas Gold Mine Venezuela

Key Economic Parameters and Results 2008 2006

Mill Through-Put Range (tonnes per day) 75,000 - 68,000 70,000

Metallugy Recovery

Plant Recovery - Gold 83% 83%

Plant Recovery - Copper 87% 87%

Net Payable Metal - Gold 82% 81%

Net Payable Metal - Copper 83% 83%

Life of Mine Production (payable metals)

Gold (million ounces) 8.35 8.41

Copper (million ounces) 1,156 1,113

Average Annual Production

Gold (ounces) 457,000 456,000

Copper (ounces) 63 60

Mine Life (years) 18.25 18.5

Initial Capital Cost ($million) 2008 2006

$ $

Mine 59.0 76.6

Mill 314.7 241.5

Infrastructure 67.8 65.8

Tailings management facility 38.3 23.8

Owner's Costs 63.4 55.6

Pre-Stripping 16.7 18.3

Indirect Costs (includes EPCM and Camp) 127.6 97.0

Contingency 43.8 59.4

Total Initial Capital $731.3 $638.0

69


Design

Pre Feasibility things

will change over time Base Case Economics 2008 2006

$ $

Metal Prices

Gold per ounce $600 $470

Copper per pound $2.25 $1.80

Cash Operating Cost Per Ore Tonne

Mining and Dewatering $2.68 $2.08

Processing 3.00 2.59

General and Administrative 0.43 0.42

Transport and Freight 0.43 0.34

Smelting and Refining 1.08 1.02

Total cash operating cost per tonne $7.62 $6.45

Cash per Ounce of Gold

Cash Operating Costs $120 $126

Exploitation Tax 22 16

Capital Cost (initial, sustaining and sunk) 135 111

Total Costs (including sunk costs) $277 $253

Total Cost (excluding sunk costs) $268 $245

Pre-Tax

Internal Rate of Return 20.5% 15.4%

Net Present Value (NPV)

@ 0% discount (billions) $2.77 $1.91

@ 5% discount (billions) $1.29 $0.7870

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(Final) Feasibility Study (FFS)

The Feasibility Study Report is a decision-making

document based on verified facts and minimum

assumptions (criteria). The report may be used for

several purposes:

Assemble a comprehensive framework of facts.

Present a detailed project description.

Forecast profitability.

Facilitate partners and/or sources of finance.

Basis for detailed engineering.



Requirements of a FS to be

bankable

A FS must be;

Credible

Definitive

Relevant

Independent


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Design

Final Feasibility high level issues Geology and ore reserves - size, shape and depth of the ore, the grade of the

ore and distribution, how homogeneous, any major faults or intrusions and hydrological reports.

Mining method and schedule surface, open cut, underground, annual production rate vs life of mine, phasing of development, envisaged ROM grade, capital equipment and manning levels required. (High production rate, high capital expenditure, shorter mine life what is the optimum?)

Infrastructure requirements - including ancillary buildings, roads, drainage,

tailings disposal, general arrangement drawings of infrastructure layout.

Metallurgy/concentrator/washery design recovery factor, concentrate grade, product quality.

Recommendations for the process plant including:

Flow diagram

Material and water balances

Equipment list (major items) together with budget quotations

General arrangement plan and elections of process plant to scale

1:100

Electrical system (line diagram)

73


Design

- high level issues continued Infrastructure, water, power, accommodation and environmental issues

source, capital and operating cost, disposal of tailings.

Permits right to mine and discharge waste and make good.

Construction schedule timing, how long to first production the quicker the better.

Logistics - of supply materials, equipment and manpower to site including an investigation of transport modes.

Identification of strategic decisions required - early ordering of long delivery items, early starts to opening of negotiations for right-of-way dispensation etc.

Preliminary programme -for carrying-out the Project.

Construction cost minimum expenditure to get the project operating, which varies depending on type and size of mine. All costs to include transport and commissioning costs, fees and all management costs except for Client's own costs.

Markets and marketing transport to market (FOB or CIF), price for product quality sold, secondary processing costs, adequate demand for product.

Financial analysis put all of the above together to determine if the project is financially viable.

74

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Combination of many errors in forecasting can be fatal for any project.

Project owner is Pegasus Gold Inc and wrote off US$353.5 million in November 1997 after closing down the project.

This write down of shareholders funds was of balance sheet items amounting to US$122.6 million of acquisition costs, US$49.4 million of deferred preproduction and development expenses and US$181.3 million for property and equipment.

75

Rudenno, 2008

Things can go wrong

Mt Todd gold mine


Case Study Mt Told Gold

Project

Commodity price overoptimism resulted in a

forecast gold price of US$385 per ounce,

including a hedging premium above

expected spot prices.

Spot prices while the project was operating

were about US$315 per ounce and the

hedging premium was small.

76

MCA - Risk Assessment in Mine Planning and Design


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77

Forecast Actual Change

Reserves grade 1.07g/tAu 0.96g/tAu -10%

Metallurgical recovery of gold 84% 74% -12%

Throughput per year 8 Mt 6.7 Mt - 16%

Crushing costs $1.36/t $2.49/t +83%

Contract mining $1.00/t $1.15/t +15%

Power costs $0.058/kwh $0.075/kwh +29%

Cyanide usage 0.68kg/t 0.86kg/t +26%

Total cash costs $11.86/t $13.58/t +15%

Cash costs per ounce gold

produced

US$287/oz US$415/oz +45%

Gold price US$385 US$315 -18%

Exchange rate, A$1.00=US$ 0.7 0.74 +6%

Case Study Mt Told Gold

Project

MCA - Risk Assessment in Mine Planning and Design Open Pit Mine Planning and Design

Open Pit Mine Planning and Design 78 of 10

NATURE & PURPOSE OF

FEASIBILITY STUDIES IN MINING

Type Scoping Preliminary Feasibility

Audience Internal Technical Mixed Professional External

Exploration Business

Development

Executive

Executives

Joint venture

Extracts to stake

holders

Boards

Financiers

Investors

Consultants

Their Interests Critical factors

Potential

Optimum project scope

Profitability

Cost of next stage

Profitability

Costs

Schedule

Risks, etc

Your Audience

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Scoping

Study

Preliminary

Feasibility

Feasibility

Study

Project Control

Estimate

Class 1

(+/- 30% - 50%)

Class 2

(+/- 25%)

Class 3

(+/- 10% - 15%)

Class IV

(+/- 5% - 10%)

Order of

magnitude

Capacity factor

estimate

Equipment factor

estimate Forced detail estimate

Definitive;

Fall out detail estimate

Cost Accuracy

Mining is a Business, but risky


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40

MINING PROJECT RISKS

TECHNICAL RISKS OH&S RISKS

POLITICAL

RISKS

ECONOMIC / FINANCIAL

RISKS

81

Participants discuss these elements of

Risk in Mining Projects.


Conclusion

Strategic planning (SP) involves developing a range

of options, carrying out some form of evaluation,

assessing criteria and decision-making.


http://images.google.com/imgres?imgurl=http://www.uniforum.org/publications/ufm/sept96/mining.gif&imgrefurl=http://www.uniforum.org/publications/ufm/sept96/mining.html&h=367&w=341&sz=90&hl=en&start=7&tbnid=G39bOsT-YZHkKM:&tbnh=122&tbnw=113&prev=/images?q=mining&gbv=2&ndsp=18&hl=en&sa=N

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Activity 2: Individual learning

Refer to worksheet 1

Development of a mining strategy: open pit and/or

underground?

Complete the task and discuss the calculations with the person(s) sitting next to you!


Module 2

OPEN PIT OPTIMIZATION


What you will learn:

Block Values and Cost calculation

Pit Optimisation techniques

Pit Optimisation Software

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42

Block Grade to Block Value

Some factors to consider:

Location of the block relative to the surface effect on

cost

Processing costs my depend on rock type

0.3%Cu -$1.13/t

Dollar Value = Revenue - Costs

86

Dollar Value = Revenues - Costs

Revenues can be calculated from:

Ore tonnages

Grades

Recoveries

Product price

Costs can be calculated from:

Mining cost

Milling cost

Overheads


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43

VALUE

= (METAL*RECOVERY*PRICE - ORE*COSTP) - ROCK*COSTM

A Formula for a Block Value used in Whittle

Calculate the value of ore block X:

200 grams of metal

100 tonnes of rock/ore

Metallurgical recovery = 97%

Selling price of metal $10.00 per gram

Cost of processing $12.00

Cost of mining $5.00

BV = [200x0.97x10 100x12 100x5] = $240

X

88

Calculating Costs

Must calculate values for:

Mining Cost per Tonne Mined

Processing Cost per Tonne Processed

Rehabilitation Cost per Tonne of Waste

Selling Cost per Unit of Product

Some Time Costs must be included


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89

Include

Any cost which is directly proportional to the tonnes

or units of product:

Fuel oil

Wages

Spare parts

Explosives

etc

Include with the appropriate activity


90

Include

Time costs which would stop if mining

stopped:

Site administration

Site infrastructure maintenance

Interest on working capital loan

Fall in resale value of equipment

Capital replacement

Truck purchase (long project)


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91

What to do with Time Costs

When mill limited

Divide annual time cost by annual mill throughput and add the result to the processing cost

When mining limited

Divide annual time cost by annual mining capacity and add the result to the mining cost N.B. Even add the mill time costs!

When selling limited ...


92

Dont Include

Time costs which continue whether

you continue mining or not

Up-front/sunk costs


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Activity 3: Individual learning


Block Values and Cost Calculation




Resource Model

Mine survey

Diluted Resource

Ore Reserve estimate

Proved and Probable

Resource estimate

Measured

Indicated

Inferred

Dilution &

ore losses

Beneficiation

factors

Operating

Costs

Economic

Parameters

Resource

Classification

Ore Reserve Model

Mining production

schedule

Beneficiation

product

Potential Ore

Reserve

Overburden

& sub-grade

Process

Parameters

Open pit optimisation

and design

Reserve

Classification

Revenue, cost and

slope parameters

position in mine

planning flow

sheet

Open Pit Optimisation

5/11/2014

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Activity 4 : Individual learning


Pit Optimisation Task 1



96

Any feasible outline has a Dollar Value. In this context

feasible means that it obeys safe slope requirements

The optimal outline is defined as the one with the highest

dollar value (Profit = Revenue Costs)

Nothing can be added to an optimal outline which will

increase the value without breaking the slope constraints.

Nothing can be removed from an optimal outline which

will increase the value without breaking the slope

constraints.

Definition of the Optimal Outline


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97

Pit Optimisation Techniques

Moving/Floating/Dynamic Cone Algorithm

Lerchs-Grossmann 2-D Dynamic Programming

Algorithm

LG 3-D Graph Theory Algorithm.

Network Analysis Algorithm

Linear Programming (integer programming)

etc


98

Floating Cone Method

Position an inverted cone, with the required slopes,

on each block with a positive value

If the total value of all blocks in the cone is positive,

mine those blocks

Repeat these steps until no cone has a positive

value

There are two problems


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99

Floating Cone Method


Courtesy: Kores Corpration

100

Floating Cone- Mining too little

-30

-80 -80

+100 +100


5/11/2014

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101

Floating Cone- Mining too much


102

Lerchs-Grossman Algorithm

Works with block values

Works with block mining precedence

Guarantees to find the three-dimensional

outline with the highest possible value


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103


Works with block values

Works with block mining precedence

Guarantees to find the three-dimensional

outline with the highest possible value


104



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LG 3d block and graph representation

Orthogonal set of blocks 2 basic geometries to represent open pit

Arrows point to the blocks that first need to be removed to access the underlying block (at the base)


106

Final Pit Design composite plan


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Pit Optimisation Task 2

Follow the example calculation of the LG pit optimisation algorithm


The algorithms to determine the final pit

limit assume that an economic value can be

assigned to each block

However, many of the costs are time costs;

it means that assigning them to blocks

requires an assumption about what is the

unitary operation that restricts production

(to express these costs in terms of that

activity)

Precautions with the OP algorithms

1) Ascribing costs to blocks


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To calculate the net value of a block one has

to assume a breakeven cut-off grade

A common assumption is to classify as ore

those blocks with a positive value and waste

those blocks with a negative value. If the

mine is the limiting operation, this misses the

opportunity to create value.

2) Assumption of a breakeven grade


There are costs that can not be estimated

without a mining plan. This is the case of waste

material, which has to be placed in a dump and

the cost will depend on the time that this

happens because of the haul distance

This can be solved by iterations!

3) Time value of money


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There are cases where blocks should be

blended with others to be classified as

ore. But that again requires a mining plan in

advance.

This can also be solved by iterations!

4) Blending requirements


Major General Mine Design Systems

Fully functional packages (with build-in CAD systems):

VULCAN

DATAMINE/CAE

SURPAC/GEMCOM

MineSight

Minex/Gemcom - WHITTLE

Micromine

CAD overlaying packages:

AutoCAD

SurvCADD/Carlson

LKAB System


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Data Import

Import

+

3D Borehole

Processing


Geological Interpretation


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57

Block Model + Grade Assessment

Block Model with Grade


Economical Model - Grade

>>> $Value

>>> Au [g/t]

Value

$$$


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Optimisation/Design

Major optimisation programs based on Lerchs-

Grossman algorithm:

Whittle FX Optimiser (stand alone)

MineMax Planner (stand alone)

Pit Optimizer (Vulcan 3D)

NPV Scheduler (Datamine)

Pit Optimiser (Surpac)


Whittle FX

Strategic Mine Planning Software

Import Block Model Pit by Pit Graph

Constrains:

Economical

Geometrical

Operational No access constrains

No haul road/ramp Open Pit Mine Planning and Design 118

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Optimal Pit


Mine Design


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60

Mine Design

Geomechanics/Geotechnical

Access constraints

Equipment selection

Ventilation network (underground)

Rehabilitation

Environmental constraints


Final Optimal Pit


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Final Optimal Pit & Pushbacks


Reporting & Evaluation


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62

Scheduling


The Pushbacks Generation


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Optimizing Production

Schedules


Optimizing Production Schedules

+ =


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Review the following technical paper:

Chanda, E.K., Spencer, E. (1999). Maximising Resource Utilisation in Open Pit Design, in Proc. 28th International Symposium on Computer Applications in the Minerals

Industry, 20-22 October, Colorado School of Mines, pp359-366, (SME-AIME, Littleton).

1) What is unique about the the approach used by the

authors? Open Pit Mine Planning and Design 129

waste dump planning



Principles of dump design and

Dump optimisation

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65

Why waste dump planning?


A strip ratio of 10:1, say, implies that for every unit of

ore mined, 10 times of waste rock is mined.

The waste rock ends up being stored in a waste

dump

Traditionally little attention has been paid to dump

design and planning, the focus being on planning of

ore extraction

It has been recognised that dump design and

planning is an integral part of pit design.

Rock flow in an open pit mine


Yu (2014)

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133 of 10

Waste Dump Design

Two main approaches:

1) Top-down dumps waste rock is dumped

over an advancing face (angle of repose)

approx 38o from horizontal. After

dumping is complete . The dump is

reshaped to its intended configuration,

usually using bulldozers.


134 of 10

Waste Dump Design

2) Bottom-up storage waste rock

is dumped in series of piles ,

and then spread to form a

relatively thin layer. Also known as paddock dumping.


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135 of 10

Waste Dump Design

Hybrid dumping whereby top

down used is used to produce

relatively thick layers (10 or 15 m,

say), which are then overlain by

subsequent equally thick layers.

This approach is safer and

requires leas reshaping.


136 of 10

Waste Dump Design

Dump progression with shortest haul first strategy


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137 of 10

Waste Dump Design

Dump design considering NAF PAF material (Yu 2013)


138 of 10

Waste Dump

Optimisation- how?

MINEMAX Software

Simultaneous pit and waste dump design

Dump modelled as blocks

WHITTLE Software

Dump optimisation as mirror image of open pit

optimisation

XPAC Advanced Destination Scheduler) Software

Module schedules rock placement


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139 of 10

Waste Dump Optimisation-

Recent Developments

Integrated modelling of dumping system (Yu 2013)


Module 3

PRODUCTION SCHEDULING



Principles of production scheduling

Scheduling Software

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Mine Scheduling (definition)

A mining schedule, which tell us when things occur, can be constructed by applying

production constraints to the mining

sequence

Basis for preparing and controlling the

mines development and production

A schedule determines the cash flow ($$$)

associated with mining.


Typical Timeline

Year

-2 -1 +1 +2

Pre-production

(Development

Construction)

Production


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Inputs

The scope of the work to be done from Mining

Layout Designs

Rates at which this work is normally prepared,

from Key Performance Indicators (KPI)

Labour working hours and rosters from

Strategic Planning module

Plant capacities, from the Strategic Planning

modules

Production schedules, Ore reserves, tonnes and

grades, recoveries and dilutions


Types of Mining Schedule

Production schedules

Long Term or Life of Mine (10+ years)

Medium Term (5 years approx.)

Short Term (3 months 2 years)

Extremely Short Term (down to a shift, or for specific jobs)

Exploration drilling schedules

Development schedules

Production drilling schedules

Equipment schedules

Labour schedules

Filling schedules

Consumable schedules

Special project schedules Open Pit Mine Planning and Design 144

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Scheduling Packages

XPAC

iGannt

MS Project

MS Excel

Whittle 4D

In-house


XPAC

Developed by Runge Software

Business focussed mine scheduling application

Specifically developed for forecasting, reserve

database and mine scheduling management of all

types of mineral deposits and mining methods

Easy-to-use tools for the adaptation, analysis and

scheduling of mineral resources

Designed for surface/underground coal mining

Has limitations in underground mining or in pits with

complex geometries


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iGantt

Developed by MineMax

Tool for open-pit and underground production

scheduling

Integrates Gantt chart, 3D visualization and

spreadsheet views of a production schedule

Used for scheduling a single operation or multiple

operations across an enterprise



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5/11/2014

75

Financial Technical Model

Plant design

Infrastructure (road, power, water, village, etc.)

Equipment selection

Capitals

Operating costs

Royalty

Tax

Revenue

NCF NPV, IRR, PB, etc.




Production Scheduling

Calculate the monthly production figures for a small gold mine


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Module 4

Cut-off grade optimization


1. Background

2. The model

3. Example 1: an hypothetical case

4. Example 2: a copper open pit mine

& mill

5. Conclusions

6. References

1. Background

This model was developed in the early

1960s by Ken Lane, a mathematician who

made his professional career in the Rio

Tinto Group

At the time, the model was used in various

mines of Rio Tinto including Palabora

mine in South Africa, and Bougainville

mine in PNG. Open Pit Mine Planning and Design 154

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2. The model

Qm

Qc

Waste

M

Cut-off gx

Concentrates

Tailings

Ore

C

Qr

R

Slag

Final product


M = Mine capacity per period (t of material)

C = Plant capacity per period (t of ore)

R = Refinery capacity per period (t of product)

Qm = Quantity of run-of-mine material (t of material)

Qc = Quantity of ore (t of ore)

Qr = Quantity of final product (t of product) = Qcgy

T = Time to mine, process or refine Qm

P = Profit

Variables used in Lanes Model


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d = annual discount rate

m = mining costs ($/t of material)

c = concentrating costs ($/t of ore)

r = refining and marketing costs ($/t of product)

f = fixed costs, per period ($/period)

s = selling price ($/t of final product)

y = overall metallurgical recovery

Models variables (cont)


The profit equation for Qm

TfQmQcQ r- sP mcr

(1a) TfQmQcyg r- sP mc

(1)

As c r

y g Q Q


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Profit from Qm

and Present Value

Qm

Grade

f

gx

Qc

W

V

V = Present value at the beginning of period T

W = Remaining present value after mining Qm


Time

P P2 P3 P4 Pn

W

V

T

0

T

d)(1

WPV

(2)


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If time T is small:

(1 + d)T 1 + dT (3)

Replacing in (2):

(4)

Re-arranging:

V(1 + dT) = P + W (5)

T)d(1

WPV


Re-arranging:

v = V - W = P - dVT (6)

Where v is the contribution that the

fraction Qm of the ore deposit makes to

the present value of the business

As such, v is the variable to maximise

when choosing the optimum cut-off

grade


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Replacing (1) in (6):

(7)

TVdfQmQcQrsv mcr

But the optimum present value V on the

right side of equation (7) is unknown

until the cut-off grade policy is optimised

This chicken and egg problem is solved

by iterations, using an arbitrary value of

V in the first iteration and stoping when V

converges Open Pit Mine Planning and Design 163

Economic cut-off grades

(7)

In equation (7), time T depends on the

stage that limits the pace at which ore is

mined

That is, the quantities Qm, Qc or Qr and

their respective capacities M, C, or R

This leads to three economic cut-off

grades:

TVdfQmQcQrsv mcr


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a) When the mine imposes a limit (M)

In this case, M

QT m

Replacing this in expression (7):

mcrm QM

VdfmQcQrsv

Max vm 0

g

vm


As Qm is given, g only affects Qc and Qr

Then g must be chosen to make (s-r)Qr - cQc

as large as possible

yrsc

gm

cc QcygQr-s

Therefore:


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b) When the plant imposes a limit (M)

In this case, C

QT c


mcrc QmQC

VdfcQrsv

Max vc 0

g

vc


In the same way, as Qm is given, g must be

chosen to maximise:

yrsC

Vdfc

gc

cc QC

VdfcygQr-s

Therefore:


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c) When the refinery imposes a limit (R)

In this case, R

QT r


mcrr QmQcQ

R

Vdfrsv

Max vr 0

g

vr


In the same way, as Qm

is given, g

must be chosen to maximise:

y

R

Vdfrs

cgr

cc QcygQ

R

Vdfrs

Therefore:


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The operation is sometimes limited by two or

eventually three stages simultaneously

Then, three balancing cut-off grades can be

introduced into the analysis

gmc: Mine-Plant

gmr: Mine-Refinery grc : Refinery-Plant

Balancing cut-off grades


gmc fully utilises mine and mill capacities;

that is, maximum stripping ratio at the mine

and throughput at the mill

Mine-mill example

Grade

f

gmc

Qm

gm gc


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Mine capacity: 650,000 t/d

Mill capacity: 150,000 t/d

gm: 0.25 %Cu

gc: 0.65 %Cu

Possible throughputs:

Cut-off % Cu

Mine t/d

Mill t/d

Grade % Cu

0.25 450,000 150,000 0.9

0.50 650,000 150,000 1.2

0.65 650,000 120,000 1.3

0.5 %Cu is a balancing cut-off


In summary, Lanes model considers six

cut-off grades:

three economic cut-off grades, and

three balancing cut-off grades

The former depend on economic factors

and capacities whereas the latter are

determined by the grade distribution that

can vary widely throughout irregular ore

bodies

None of these considers mining costs!


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The overall optimum is one of the six cut-

off grades already defined:

1) gm

2) gc

3) gr

4) gmc

5) gmr

6) grc

To assess which one is the optimum it is

best to consider each pair of stages in

turn

Optimum cut-off grades


To see which one is the optimum it is best

to plot the value functions considering

each pair of stages in turn

Mine-Concentrator

mcrm QM

VdfmQcQrsv

mcrc QmQC

VdfcQrsv


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88

g

v

gmc gc gm

Gmc = gm vc vm

g

v

gmc gc gm

Gmc = gmc vc vm


g

v

gmc gc gm

Gmc = gc

vc vm

In a similar way, by considering the other

pair of stages, it is possible to obtain Gmr

and Grc


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g

v

gmc gc gm

vc vm

vr

gr gmr grc

The overall optimum cut-off grade is:

G = Middle value (Gmc,Gmr,Grc)


Mine capacity (M) = 100

Plant capacity (C) = 50

Refinery capacity (R) = 40

Mining costs (m) = 1

Concentrating costs (c)= 2

Refining costs (r) = 5

Fixed costs (f) = 300

Selling price (s) = 25

Overall recovery (y) = 100 %

Annual discount rate (d)= 15 %

3. Example 1: an hypothetical case


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Grade-tonne relationship

Grade interval

Quantity

0.0 0.1 100

0.1 0.2 100

0.2 0.3 100

. .

.

0.9 1.0 100

1000

g

f(t)

100

0 0.5 1.0



Cut-off Tonnage Ratios

Mine Mill Grade Ref. M/C M/R C/R

0.0 1000 1000 0.50 500 1.00 2.00 2.00

0.1 1000 900 0.55 495 1.11 2.02 1.82

0.2 1000 800 0.60 480 1.25 2.08 1.66

0.3 1000 700 0.65 455 1.43 2.20 1.54

0.4 1000 600 0.70 420 1.67 2.38 1.43

0.5 1000 500 0.75 375 2.00 2.67 1.33

0.6 1000 400 0.80 320 2.50 3.13 1.25

0.7 1000 300 0.85 255 3.33 3.92 1.18

0.8 1000 200 0.90 180 5.00 5.56 1.11

0.9 1000 100 0.95 95 10.00 10.53 1.05

M/C = 100/50 = 2.00 gmc = 0.50

M/R = 100/40 = 2.50 gmr = 0.45

C/R = 50/40 = 1.25 grc = 0.60



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Economic cut-off grades

0.10

yrs

cgm

0.40

yrsC

Vdfc

gc

0.16

yR

Vdfrs

cgr

For V = 0



Gmc = Mid (0.10, 0.40, 0.50) = 0.40

Gmr = Mid (0.10, 0.16, 0.45) = 0.16

Grc = Mid (0.16, 0.40, 0.60) = 0.40

G = Mid (0.16, 0.40, 0.40) = 0.40


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Intermediate mine plan

Year Cut-off Mine Mill Ref. Profit

1 0.4 83.3 50 35 216.7

2 0.4 83.3 50 35 216.7

. . . . . .

. . . . . .

. . . . . .

12 0.4 83.3 50 35 216.7

P = (25 - 5)35 250 183.3 3001

P = 216.7

PV@12y and 15% = 1174


Second iteration

0.10

yrs

cgm

0.58

yrsC

Vdfc

gc

0.25

yR

Vdfrs

cgr

For V = 1174


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Gmc = Mid (0.10, 0.50, 0.58) = 0.50

Gmr = Mid (0.10, 0.25, 0.45) = 0.25

Grc = Mid (0.25, 0.58, 0.60) = 0.58

G = Mid (0.25, 0.50, 0.58) = 0.50


A new mine plan...

With the new cut-off grade of 0.5, a new

mine plan can be developed but this time

changing the present value from year to year

If annual profits are discounted to time 0 and

added up, it gives another estimate of V

If the difference of the initial and final value

of V exceeds a defined tolerance threshold,

the whole process is repeated


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Annual profit for the first year...

P = (25 - 5)37.5 250 1100 3001

P = 250

PV@ 10y and 15% = 1255

For a 0.5 cut-off grade, the annual profit and

present value is as follow:


Optimum mine plan and cut-off grades policy

Year Cut-off Mine Mill Ref. Profit PV

1 0.50 100 50 37.5 250 1255

2 0.50 100 50 37.5 250 1194*

3 0.50 100 50 37.5 250 1123

4 0.50 100 50 37.5 250 1041

5 0.50 100 50 37.5 250 947

6 0.50 100 50 37.5 250 840

7 0.50 100 50 37.5 250 716

8 0.49 97 50 37.1 245 573

9 0.46 93 50 36.5 238 414

10 0.41 89 50 35.9 229 238

11 0.41 21 13 8.8 55 45

* W = V(1+d) - P

W = 1255 1.15 250 = 1194

1000 513 380.8 2517

PV @ 11y and 15%= 1256


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Relevant data: Mine capacity (M) = 18.9 Mt/a

Plant capacity (C) = 7.2 Mt/a

Mining costs (m) = 0.85 $/t material

Milling costs (c) = 3.7 $/t ore

Fixed costs (f) = 3.5 M$/a

Copper price (s) = 2205 $/t Cu ($1.0 /lb)

TC/RC & selling cost (r) = 705 $/t Cu ($0.32 /lb)

Overall recovery (y) = 85 %

Annual discount rate (d) = 10 %

4. Example 2: a copper open pit mine & mill


A set of four pushbacks

B

D

C

A


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Input to the model: four scheduled, nested pits

(periods) from a preliminary mine plan

1

1

1

3

2

2

3

4

4

3

PP


Grade-tonnage relationship for the four pits

Cut-off Period 1 Period 2 Period 3 Period 4

% Cu Mt % Cu Mt % Cu Mt % Cu Mt % Cu

0.0 20.3 1.05 36.5 0.79 56.3 0.57 80.1 0.59

0.2 18.7 1.13 30.1 0.92 40.8 0.76 60.4 0.77

0.4 15.3 1.32 24.4 1.08 28.5 0.97 50.2 0.87

0.6 12.9 1.47 19.7 1.22 21.7 1.11 38.3 0.98

0.8 11.0 1.61 13.7 1.45 15.1 1.30 22.7 1.18

1.0 8.6 1.80 10.2 1.64 10.0 1.49 14.6 1.35

1.2 7.1 1.95 7.6 1.83 6.9 1.67 9.0 1.49

1.4 5.9 2.08 5.6 2.02 4.4 1.88 5.0 1.65

1.6 4.4 2.27 4.0 2.24 2.7 2.11 2.9 1.75


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Output for a Base case

Year Period 1 Cut-off (% Cu)

Mine (Mt)

Mill Ratio (W/O)

Profit (M$)

PV (M$) (Mt) (% Cu)

1 1 0.85 14.2 7.2 1.67 0.97 110.3 475.5

2 1 0.78 6.1 3.4 1.59 0.82 49.6 412.8

2 2 0.78 9.8 3.8 1.43 1.56 44.8 412.8

3 2 0.72 16.8 7.2 1.37 1.34 81.3 359.6

4 2 0.67 9.9 4.7 1.31 1.13 50.4 314.2

4 3 0.61 6.7 2.5 1.12 1.62 19.4 314.2

5 3 0.61 18.9 7.2 1.12 1.62 56.3 275.8

6 3 0.60 18.6 7.2 1.11 1.58 55.8 247.0

7 3 0.56 12.1 4.9 1.08 1.45 36.5 215.9

7 4 0.56 4.5 2.3 0.96 0.98 14.9 215.9

8 4 0.53 13.6 7.2 0.94 0.89 44.5 186.1

9 4 0.50 13.1 7.2 0.92 0.82 43.3 160.3

10 4 0.47 12.6 7.2 0.91 0.75 42.4 132.9

11 4 0.44 12.1 7.2 0.89 0.68 41.4 103.9

12 4 0.41 11.6 7.2 0.87 0.61 40.2 72.9

13 4 0.37 11.2 7.2 0.86 0.55 38.9 39.9

14 4 0.33 1.5 1.0 0.84 0.50 5.1 5.0

193.2 94.6 1.11 1.04 PV = 475.5


Output for an expanded case (Mill from 7.2 to 9.0 Mt/a)

Year Period 1 Cut-off (% Cu)

Mine (Mt)

Mill Ratio (W/O)

Profit (M$)

PV (M$) (Mt) (% Cu)

1 1 0.78 16.3 9.0 1.59 0.81 131.8 521.2

2 1 0.71 4.0 2.3 1.53 0.71 33.1 441.6

2 2 0.67 14.0 6.7 1.30 1.10 71.3 441.6

3 2 0.65 18.5 9.0 1.29 1.05 95.4 381.3

4 2 0.60 4.1 2.2 1.22 0.86 22.1 324.0

4 3 0.45 14.2 6.8 1.00 1.10 46.6 324.0

5 3 0.45 18.9 9.0 1.00 1.10 62.0 287.7

6 3 0.45 18.9 9.0 1.00 1.10 62.0 254.4

7 3 0.45 4.2 2.0 1.00 1.10 13.7 217.9

7 4 0.51 12.9 7.0 0.93 0.84 43.2 217.9

8 4 0.48 15.9 9.0 0.91 0.76 54.1 182.8

9 4 0.45 15.2 9.0 0.89 0.69 52.9 146.9

10 4 0.42 14.6 9.0 0.88 0.62 51.5 108.8

11 4 0.38 14.1 9.0 0.86 0.56 50.0 68.1

12 4 0.34 7.4 4.9 0.84 0.51 26.4 25.0

193.2 103.9 1.06 0.86 PV = 521.2


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Conclusion for this case

The Base Case produces a declining cut-off

grade policy starting at 0.85 %Cu and yielding

a PV of $ 475.5 million

The Expanded Case lowers the initial cut-off

from 0.85 to 0.78 %Cu and increases the PV

by $46 million from $475.5 to $521.2 million

If the expansion capital investment is less than

$46 million, then it is worth going ahead


5. Concluding remarks

Lanes cut-off grade model is a first attempt to

define economically what material is ore in a

life-of-mine (LOM) plan

It requires a holistic view of mining in that the

optimisation needs a preliminary LOM plan.

That is, a final pit limit, pushbacks design and

scheduling based on a breakeven cut-off - the

mine or plant cut-off grade, for instance


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Cutoff Grade Optimisation

Follow the calculations to the problems


Lanes model considers various variables as

fixed input capacities, and downstream cut-

offs such as metallurgical recovery at the mill

Most recent developments have expanded the

model to include some of these variables and

handle them simultaneously

When the problem becomes too complex, it is

solved using other mathematical tools, integer

linear programming being one of them


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6. References

Kenneth F. Lane - The economic definition of ore, Mining

Journal Books, London 1988

Kenneth F. Lane - Choosing the optimum cut-off grade,

Colorado School of Mines Quarterly. Vol. 59-4, 1964, pp. 811-

829

Blackwell, M. Some aspects of the evaluation and planning of

the Bougainville copper project, Decision-Making in the

Mineral Industry, CIM Special Vol 12, 1971 pp. 261-269


Module 5

Mine Planning Software


202

Software Packages

Categories

Capabilities

Providers

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Common Software Packages


203

Categories of Mining Software


204

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Mapping Software


205

Geological & Data managent


206

Source: (Sable, 2013)

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Geological Modelling/

Resource Estimation


207

Drill hole display (Source: Geovia, SUPARC)

Geological Modelling/

Resource Estimation


208

Ore body model(Source: CAE, STUDIO 3)

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Mine Design


209

Pit Design (Source: Maptek, VULCAN)

Planning and Scheduling


210

Pit Design (Source: Geovia, MineSched)

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Financial Evaluation


211

Financial Analysis Software (RungePincockMinarco)

Optimisation/Risk Analysis


212

Pit Optimisation (Geovia, WHITTLE)

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Monitoring & Control


213

Truck Dispatching (Modular Mining System; (DISPATCH)

Simulators


214

Coal Mining Simulator (Immersive Technologies)

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Virtual Reality


215

ViMine VR Software 3D Ore body model

Summary


216

Advances in Computer technology has

made it possible to model complex mining

environments

Most widely software is for Mine Design &

Planning

Further developments in simulation and

risk modelling

Mining software harmonisation by

suppliers

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Module 6

mine to mill optimisation


217

Concept embraced and practiced by mining

companies

The philosophy is base on:

Characterise

Track

Measure

Model

Potential to save mining companies thousands of

Dollars


Drilling

Blasting

Loading

Hauling

Milling (Crushing, grinding)

Examine total system with regard to cost,

productivity, product quality, optimisation...

Mine production system processes

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Loading: increased fragmentation => higher rate of shovel productivity, hence lower costs per BCM.

Hauling: Truck production per hour will increase with

greater fragmentation due to faster shovel loading rates.

Reduced cycle time.

Crushing: Lower crushing costs result from increased

fragmentation as more material pass through as under

size.

Drilling and blasting costs are harder to relate to

fragmentation).


Unit costs as a function of the degree of

fragmentation

Systems optimisation:

Optimum Fragmentation Curves

Degree of fragmentation

Overall Cost Curve

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Blasthole Drilling

Bore diameter

Hole deviation monitor

Geophysical data

Real time drilling data

Exploration Drilling

Intact rock data

Mineralogy data

Fracture frequency data

Ore body modeling and pit design

Blast Modelling Displacement model Fly rock Heave mechanics

Blast Design

Pattern layout

VOID

Powder factor

Explosive

Muckpile properties

Size distribution* Voids ratio* LCM Visualization Density

S01U264007

0

20

40

60

80

100

120

1 10 100 1000

Size (mm)

Pe

rce

nta

ge

Pa

ssin

g (

%)

S01U264007

35.2Mtpa ROM Target

Excavation/Loading

Digability* Dig rate* Dipper design Power consumption Swing analysis Autonomy

Hauling

Payload data Voids ratio* LCM TKPM rating Autonomy Routing data

Crushing/grinding

Energy data Bond's Work Index Settings

Process

Optimization

Blast design,

Load-Haul


Examine individual components and the whole system

Goal: achieving a prescribed level of fragmentation at

minimum cost

In-situ ore with particle size considered to be very large

and reducing to size in the order microns (eg -80 mesh).

Measuring Fragmentation, how?

Diggability (BCM/HR)

Size distribution of muckpile (WIPFrag Software), Split-Desktop software

Photographs are taken from muck pile, digging

face, moving truck, etc.

Optimum Fragmentation

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Fragmentation evaluation

Measurement of parameters- correlate with

fragmentation

Photographs are taken from muck pile, digging face,

moving truck, etc.

Crusher monitoring - energy, feed, product size,

throuputghput

Shovel monitoring- load, wait, down time, swing, power

Drilling and Blasting SubSystem


Case Study

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Case Study

Modeling Muck Pile Fragment Size to Optimize

Excavator Productivity in Open Pit Mining

Prominent Hill Copper Mine, South Australia


Prominent Hill

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Prominent Hill

Muckpile Image Analysis using SPLIT DESKTOP:

The split desktop system uses digital image

analysis technology to convert an image

captured from a digital camera to a distribution

of defined areas within the photograph.

The software was developed from a system of

manual image analysis where a photographic

image was manually delineated and the diameter

of each particle measured


Prominent Hill

Camera

Photo of muckpile

Photo collection and scale placement on flitch face.

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Prominent Hill

Blast master 10040RL


Prominent Hill

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Prominent Hill


Prominent Hill

Our modelling of the excavator production rates

has suggested that P80 of 800 mm would be the

optimal size to maximise excavator productivity

at 6300 t/hr.

However due to mine machinery and crusher

constraints we believe a revised figure of 600

mm would be more appropriate

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Module 7

Equipment Selection


233

Simulation modelling using GPSS/H Case Study

Cost Estimation (Capital & Operating)

Study Background

Methodology

Results

Discussion

Conclusion

Recommendations

Simulation and Animation of an

Australian Surface Mine


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Wilcherry Hill Iron Ore Mine

The Wilcherry Hill project is

located 30 km north of the

township of Kimba in South

Australia.

The Wilcherry Hill project

comprises of four tenements

and covers an area of 976

square kilometres.

The tenements are EL4162-

Wilcherry Hill, EL4286-Valley

Dam, EL4421- Peterlumbo,

EL3981-Eurilla Dam.


Development at Wilcherry Hill is proposed in three phases; stage 1, 2 and 3.

Stage 1 will be the focus of this project

Comprises mining, crushing and export of Direct Shipping Ore (DSO)

Ore sourced from the upper parts of the mining pits.

Project Development


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Methodology

Aim

Simulation and animation model using the Stage

1 layout of the mine

Determine the optimum number of shovels and

trucks required for this mining scenario

Provide the company with a model they can use

for many what if? scenarios.


Programming in GPSS/H

Approximately 1,200 lines of computer code were

used to model this mining scenario

Over 60,000 command lines were used to generate

this animation


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Methodology

GPSS/H Simulation Main Commands


Methodology Variables, User Information and Generate

Variables:

REAL &X,&Y,&Z,&A,&B,&C,&D,&E,&F,&G,&H,&I

User Information:

PUTSTRING (' ')

PUTSTRING ('HOW MANY TRUCKS?')

PUTSTRING (' ')

INTEGER &TRUCKS

GETLIST &TRUCKS

Generate:

GENERATE 3,,0,&TRUCKS,,12PH,12PL


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Methodology

Animation


Methodology

Mine Layout (Draw, Class and Paths)


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Methodology

Run


Methodology

Animation


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Methodology Animation


Results

HD 785

EMPTY: 72 t

LOADED: 164 t

LOADED SF: 147.6 t

ORE WEIGHT: 75.6 t

STRUCK BODY CAPACITY: 40 m3

ORE SPECIFIC GRAVITY: 4

FULL STRUCK LOAD ORE WEIGHT: 160 t

HOURS PER SHIFT: 8

Assumptions


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Results

Ore Results

TRUCKS: 3 4 5 6 7

ORE DUMPS PER SHIFT: 9 13 17 20 23 DUMPS

STOCKPILE DEPOSITION PER SHIFT: 1440 2080 2720 3200 3680 T

STOCKPILE WITHDRAWAL RATE: 180 260 340 400 460 T/HR

COMPARISON (IRONCLAD): 291 T/HR


Results

Ore Results


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Results

Waste Results

TRUCKS: 3 4 5 6 7

WASTE DUMPS PER SHIFT: 68 87 104 123 142 DUMPS

DUMP DEPOSITION PER SHIFT: 5140.8 6577.2 7862.4 9298.8 10735.2 T

DUMP RATE: 642.6 822.15 982.8 1162.35 1341.9 T/HR

COMPARISON (IRONCLAD): 885 T/HR


Results

Waste Results


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Conclusion

GPSS/H Simulation and Animation

Number of shovels: one shovel

Number of trucks: five trucks and possibly an extra standby truck

TALPAC simulations

Number of shovels: one shovel

Number of trucks: six trucks


Acknowledgements

Postgraduate Students:

Sophie Mellor

Jian Liu


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Cost Estimation

Capital Costs

Operating Costs


254 of 10

Capital cost estimation: general

considerations

Indicative capital cost estimates

Based on empirical data from other

projects

Estimates are within +/- 30% accuracy

Suitable for scoping or pre-feasibility

studies

Often use rules-of-thumb to estimate

costs

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Capital cost estimation: general considerations:

Indicative capital cost estimates (cont.)

The sixth-tenths rule (Mular, 1978):

Cost 1 / Cost 2 = (Capacity 1 / Capacity 2)0.6

Capacity 2 and Cost 2 relate to a known similar operation in a similar environment

Capacity 1 relates to the operation being studied

Cost 1 is then estimated

Annualised cost per tonne rule:

Annualised cost per tonne of a known operation

= {Total capital cost} {tonnes per year}

Use this factor directly to estimate capex for another, similar operation.



considerations

Cost indices

Most cost estimations are based on historical

data available to the estimator.

These data date and cost indices can be used to

update them:

Cost now = {cost then}{cost index now/cost index

then}

Indices available from Cost Guides


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257 of 10


considerations

Working capital

This is the capital component of operating

costs needed to support the operation

prior to substantial revenue inflows.

Often underestimated and can result in

project failure.

Sometimes a factor (such as 10% of fixed

capital cost) is applied. However a more

detailed analysis is usually good practice.

258 of 10


considerations Options for capital equipment

Contract mining

capital not available;

short duration;

specialist skills required; and/or

specialist equipment required.

Hired equipment

machine only and hirer responsible for fuel, oil, servicing and operation (dry hire); or

full hire (all inclusive), usually hourly rate with standby rate.


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considerations Ownership cost

Fixed cost per hour irrespective of whether

the machine is working or not

It is a function of:

purchase price

cost of any extras

freight charges

tyre costs

resale value

depreciation period



considerations Ownership cost (cont.)

Straight-line depreciation formula:

D = (P - R) / (N.H) where D is depreciation per

hour, P is purchase price, R is residual value, N is

usefu

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