Gu a Whittle

MIME 513 – Mine Planning Optimization under Uncertainty – Fall 2012

Lecturer: R. Dimitrakopoulos

Project Start

Optimization in Mine Design using Whittle Software

Due date: October 3rd

2012

Early bird submission bonus – by September 23rd

2010: 10%

Late submission penalty: 10% per day

OUTLINE

1. Introduction

2. Task

3. Data Files

4. Instructions



1. Introduction

Assignment 1, part of project, covers the following topics:

1. Definition of the ultimate pit limit.

2. Determining nested pit shells.

3. Designing pushbacks.

4. Effects of extraction sequence of ore/waste blocks on production scheduling and

long term planning.

Concepts behind Whittle Nested Pits

Whittle uses a Model File containing details of the contents of each block, but, for

optimization purposes, we need a single value for each block. This value is the cash flow

(positive or negative) that would result from mining the block. For optimization purposes

it is important to assume that the block has been uncovered. It is unnecessary to allow for

stripping costs, because the optimizer does this implicitly. If we calculate the block

values for a particular model we will get a certain set of block values that, when used in a

pit optimization, will lead to a particular pit outline, the optimal outline.

Example 1

For the purpose of this example, assume the pit outline is outline "A" in the following

diagram.

Figure 1. Pit outline obtained from a single optimization.

Within an optimal outline, every block is "worth mining". Each block consists of zero or

more parcels and, possibly, some undefined rock that can be regarded as another parcel.



The resultant cash flow from mining a block consists of the sum of the cash flows

generated be mining the block’s parcels. A parcel’s cash flow depends on the way we

treat the parcel (i.e. mill, leach, etc.) and the associated prices and costs with the method

of treatment. An increase in all commodity prices while keeping the costs constant may

cause the parcel to be treated differently (e.g. it may now be processed rather than treated

as waste); in this case, the cash flow will always either stay the same or increase.

Increasing the prices will not decrease the cash flow obtained from mining a given parcel.

Thus, if we increase the prices, the value of every block within outline A will increase or

stay the same. No block value will go down. Consequently, every block within outline A

is still worth mining.

Example 2

In addition, if we do another optimization using the new values, the new outline (shown

as outline B below) is certain to include the whole of A. It may also include extra blocks

that were not worth mining before, but which are now worth mining.

Figure 2. Pit outlines obtained from two optimizations.

The Whittle Pit Shells node (Optimization program, FXOP)

If we step the prices through a series of values, doing an optimization for each, we obtain

a set of nested pit outlines, and this is, in effect, what the Pit Shells node in Whittle does.

It multiplies all of the prices by a series of 50 to 100 "Revenue Factors" ranging,

typically, from 0.3 to 2.0, and produces a pit outline for each factor. The reason for

producing outlines for the smaller values of Revenue Factor is that we want to produce

inner pit shells that highlight the best positions to start mining and to assist with the

sequencing. The outlines are often very close together and form an almost continuous

"spectrum", where the change in tonnage from one outline to the next is quite small.

However, if the grade increases sharply with depth or the ore body is discontinuous, large

tonnage differences between adjacent pits can occur. Since all the outlines obey the pit



slope requirements, it is simple to determine which sequences are feasible when mining

out a particular pit.

Example 3

Figure 3. Schematic of nested pits.

In Figure 3, if pit 5 is the ultimate pit, we can clearly mine in the sequence a, b, c, d, e, f,

g, h, etc. If the pits are sufficiently far apart to give working space, another possible

sequence is a, f, b, g, k, c, etc. Regardless, given a set of nested pits, these sequences are

clearly defined and easy for the computer to trace, and thus can be used to show various

mining schedules in order to obtain projected tonnages, grades and cash flows. Although

each set of outlines is only strictly optimal for a particular set of costs, their usefulness

goes far beyond this. Provided that the costs used are of the same order, another

optimization run with different costs will usually produce a set of pits of similar shape,

but are shifted relative to those from the first run. For example, pit number 20 from one

run may be very similar to pit number 25 from the previous run. It is therefore reasonable

to simulate mining with wide ranges of prices and costs using the same set of nested pits.

Once a set of costs has been settled on, a final optimization using those costs and a

repeated simulation can be run as verification.



2. Task

Find the optimal ultimate pit limits, design pushbacks and generate a Life-of-Mine

(LOM) production schedule for a copper deposit, so as to maximize its Net Present

Value. Report all findings and justify your choices. For this task, the Whittle software

must be used along with the parameters provided in Table 1 and the orebody models in

the files described below. All deliverables for this assignment are discussed in this

section; for information on the related files and steps, refer to the following sections.

Table 1. Parameters for the optimization of a copper deposit.

Slope angle 45

Selling price 1.9$/lb

Selling cost 0.4$/lb

Mining cost 1$/tonne

Processing cost 9$/tonne

Recovery 90%

Cut-off 0.3% Cu

Model Cu unit Tonnes

Processing capacity 7.5 M tonnes

Extraction capacity 28 M tonnes

Discount rate per period 10%

Step 1: Defining the ultimate pit limit

Define the final pit by choosing amongst the available nested pit shells generated by

Whittle.

Deliverables from Step 1:

a. A pit-by-pit graph of undiscounted cash flow per pit shell, where the pit number is

plotted on the X axis and the net economic value on the Y axis.



b. A pit-by-pit graph of discounted cash flow per pit, where the pit number is plotted

on the X axis and the discounted economic value on the Y axis.

c. Pit-by-pit graph of recovered metal, ore and waste where the pit number is plotted

on the X axis and the metal on the Y axis.

d. Plot the required graphs using bar style.

e. All choices made need to be justified and implications briefly explained.

Step 2: Design pushbacks given the ultimate pit limit in Step 1

Using the final pit as defined in Step 1, use the automatic pushback selection in Whittle

to choose the pushback design. Try at least two different and meaningful numbers of

pushbacks and assess the possible implications on the final NPV of the mine; explain the

differences and related effects.


a) A table that associates a pushback to its NPV.

b) Report in pushback-by-pushback graphs ore, waste, metal and cash flows.

c) Discuss the implications of the number of pushbacks used and what they physically

represent.

d) All choices must be justified and implications briefly explained.

Step 3: Generate the LOM production schedule of the mine

Using the ultimate pit and pushback design from Steps 1 and 2, generate the LOM

production schedule. Please use the same processing and extraction capacities as in Table

1.


a) Produce the LOM production schedule and report all related graphs (ore, waste,

metal production, and cumulative NPV) for the mine.

b) Describe the differences among the available schedule generating options: Milawa

NPV, Milawa Balance and fixed lead.

c) All choices must be justified and implications briefly explained, including the

selection of the scheduling option.



Deliverable for Assignment 1:

A properly documented report that amalgamates the

deliverables from each of the three Steps above, for

the mine’s yearly pit design and mine planning study.



3. Data Files

The folder named “Assignment 1” contains the following folders and files:

Assignment 1: This contains a folder named MOD FILES and a description of the

procedure to carry out the expected tasks involved in Assignment 1.

The MOD FILES folder contains a single estimated (kriged, deterministic) orebody

model and a parameter file.

*.mod (Orebody block model file) is a type of file that contains the specification of the

block model of the deposit such as block coordinates, metal grade, ore and waste

tonnage, etc…

Figure 4. Example of a mod file when opened in a text editor.

The parameter file contains the following general information, for further details please

consult Whittle’s help documents (can be accessed within the software).

The parameter file given for this assignment consists of the following information:

Dimensions of a block are the X, Y and Z directions, respectively.

Origin coordinates related to the origin of the model framework is at the outer

corner of the block with coordinates 1,1,1.

Dimensions of the model framework are expressed as the number of blocks in the

X, Y and Z directions, respectively.



While the supplied parameter file does not contain this information, it is entirely possible

that it contains the following information:

General formatting requirements provide the number of decimal places to be used

for the input and output of various quantities, other than those associated with

specific elements.

Active blocks indicator specifies which blocks you want Whittle to work on when

doing the optimizations. There are three possible indicators, and are defined as

follows:

o Active blocks indicator of 1: all of the blocks in the model framework are

considered for mining.

o Active blocks indicator of 2: only the blocks within sub-regions are

considered for mining. The sub-regions do not need to fill the model

framework. If blocks occur in the Model File in regions not included in a

sub-region, they are rejected. An active blocks indicator of 2 can be useful

in certain unusual circumstances.

o Active blocks indicator of 3: only blocks provided in the Model File are

considered during optimization. That is, the rest of the blocks in the model

framework are completely ignored.

Restart interval lets you specify the time between dumps. Dumps refer to the Pit

Shells node which periodically dumps all of the data from memory to its Work

File to enable a later restart. This can be extremely helpful if, for example, a long

optimization run is terminated because of power failure. If the restart interval is

left blank, restart dumps occur every two hours.

Reference mining cost is the cost of mining waste of undefined rock-type at the

Reference Block.

Cost of mining waste of a defined rock-type at the Reference Block is obtained by

multiplying the Reference Mining Cost by the appropriate rock-type mining CAF

(cost adjustment factor).

Cost of mining waste of any type at a particular block is obtained by multiplying

the cost of mining the same rock as waste at the Reference Block by the positional

mining CAF for the block in question.

Mining dilution factor - Example: A five percent dilution would be effected by a

mining dilution factor of 1.05. The dilution is applied by increasing the tonnage of

mineralized parcels, regardless of whether there is any waste (non-parcel tonnage

or parcels with no elements) in the block. This can lead to a negative waste

tonnage for an individual block and, in regions of the pit that are entirely

mineralized, negative stripping ratios are possible.

Mining recovery factor is applied to take into consideration the loss of ore due to

mining at the edge of the orebody or during transportation to the mineral



processing plant. The mining recovery factor allows an overall mining recovery to

be applied.

General default block tonnage is used by the Reblocked Block Model node and by

the Pit Shells node (where the active blocks indicator is set to 1 or 2) for blocks

that are not specified in the Model File. Default block tonnages can be blank

(meaning undefined), or a value that is zero (to represent air), or positive.

Ore selection method flag controls how Whittle selects ore for processing from

the available parcels. There are two possible flag settings: 1 and 2.

o Ore selection method flag set to 1 – Selection by cut-off

Ore is selected by comparing the grades of the material with pre-

calculated processing cut-offs. If the material does not satisfy the

cut-offs, it is treated as waste.

If more than one processing method is applicable, the grades are

compared with the cut-offs of each in turn, in the order in which

they are specified in the Parameters File.

o Ore selection method flag set to 2 – Selection by cash flow

Ore is selected by comparing the cash flow that would be produced

by processing it, and the cash flow that would be produced by

mining it as waste. If the cash flow from processing it is higher, the

material is treated as ore. If not, it is treated as waste. If more than

one processing method is applicable, the one that produces the

highest cash flow is used.

Air flags are used to specify the treatment of air blocks or undefined blocks in the

model:

o Air flag A controls whether air blocks are included or excluded, during pit

optimization. There are two possible flag settings: 1 (included) and 2 (not

included).

o Air flag B controls which air blocks from the Model File are included in

the Results File. There are three possible flag settings: 1, 2 and 3.

o Air flag B set to 1: air blocks are not included in the Results File,

regardless of whether air blocks were included or excluded during

optimization.

o Air flag B set to 2: only those air blocks are included in the Results File

that would be "mined" as part of the largest pit extended into the air.

The positional mining CAF flag controls whether or not the positional mining

CAFs are used by the Pit Shells node and the Analysis nodes (Analysis program).

There are two possible flag settings: 1 and 0. Positional mining CAF flag set to 1:

the positional mining CAFs in the Model File are used by the Pit Shells node and

the Analysis nodes. Positional mining CAF flag set to 0: the positional mining



CAFs in the Model File are not used by the Pit Shells node nor are the Analysis

nodes.

The positional processing CAF flag controls whether or not the positional

processing CAFs are used by the Pit Shells node and the Analysis nodes. There

are two possible flag settings: 1 and 0. Positional processing CAF flag set to 1:

positional processing CAFs in the Model File are used by the Pit Shells node and

the Analysis nodes. Positional processing CAF flag set to 0: positional processing

CAFs in the Model File are not used by the Pit Shells node nor the Analysis

nodes.

The print unprocessed mineralisation flag controls whether or not the Pit Shells

node and the Analysis nodes report the total tonnage and element content of any

mineralised material that is mined but not processed. These quantities can be

useful when reconciling the results of different runs. There are two possible flag

settings: 1 and 0.

Revenue Factor values in the pit shells node are used to scale base case prices up

or down, in order to control which nested pits are to be produced.

Regarding Sub Regions; Parameter Files with no sub-regions are valid, but then

the Slope Set node will demand an Additional Arcs File, which will have to

contain all of the required arcs.

Block limits specifies the size and location of a sub-region by its lowest and

highest block numbers in the X, Y and Z directions.

Sub-region default block tonnage

Default block tonnages are used by the Reblocked Block Model node and by the

Pit Shells node (where the active blocks indicator is set to 1 or 2) for blocks that

are not specified in the Model File. If the density of rock varies within the model

framework, but the variation can be simulated by allocating different default

block tonnages to different sub-regions, then sub-region default block tonnages

can be useful.

Slope angle should be provided along with information of the bearing and the

slope.

Bearings are expressed in degrees, clockwise from the positive Y direction –

usually north. It is very important to note that bearings are given instead of wall

positions. Any walls at right angles to the bearings, in a particular slope region,

will have the given slope applied.

Slopes are expressed in degrees from horizontal.

Number of benches to consider for arc generation may control the accuracy of

slope reproduction. The more benches that you specify, the greater the accuracy,

and the longer the optimization will take.

Grade dependent expression information must include an expression identification

code, the expression usage and the definition of the expression.



The element type code is an alphanumeric code of from 1 to 4 characters which

identifies a particular element in the model. It is not case sensitive. Examples:

GOLD, Cu.

The position in the Model File specifies the position of the element data in the

Model File.

The element formatting requirements provide the number of decimal places to be

used for the input and output of element quantities in a parcel, total quantities and

grades.

The selling cost per unit is the cost involved in selling a unit of the element,

where a unit is defined by the values used for quantities of the element in the

Model File.

The price per unit is the price for a unit of the element where a unit is defined by

the values used for quantities of the element in the Model File. It is used with the

Revenue Factors to determine element prices for different pit shells.

Rock-type information must include the rock-type code, the rock-type mining

CAF, the rehabilitation cost per tonne and the processing throughput factor.

The rock-type code is an alphanumeric code of from 1 to 4 characters which

identifies a particular rock-type in the model. It is not case sensitive. Examples:

OXID, SULF, WTHR.

The rock-type mining CAF is the ratio between the cost of mining this type of

rock as waste, and the cost of mining undefined blocks.

The rehabilitation cost is the cost associated with rehabilitating waste dumps

chemically, visually and ecologically. This cost is applied if the material is treated

as waste, but not if it is processed.

Processing-method/rock-type for open pit mining must include processing method

code, rock-type code, processing cost and element information. The processing

method code is an alphanumeric code of from one to four characters. It identifies

the processing method to be used. It is not case sensitive. Examples: MILL,

HEAP, CIL.

The rock-type code, which is not case sensitive, must be one of the codes defined

for a rock-type. The pairing of the method and type codes indicates that parcels of

this rock-type may be processed by this processing method, if it is economic to do

so. If a rock-type, even one containing elements, occurs in the Model File, but is

not paired with a processing method here, it will be treated as waste.

Processing cost the effective processing cost is used for calculating cash flows as

well cut-offs.

Element type code must be one of the codes defined for an element above.

Cut-off control flag dictates whether or not the element(s) are cut-off controlled.

This is only relevant when ore selection is by cut-off.



Element processing cost per unit is the cost that can be calculated based on the

units of each element input into the process, where a unit is defined by the values

used for quantities of the element in the Model File. It is in addition to the general

processing costs.

Processing recovery fraction is the processing recovery (e.g. 0.93) at high grade

for this element.

Processing recovery threshold is a grade that is subtracted from the actual grade

of each parcel before the processing recovery fraction is applied.

It is important to note that although the information above is a list of what may be

contained in a parameter file, the inclusion of all the above parameters is not required for

it to serve its purpose.



4. Instructions

The computer session of this first part focuses on the basics of using the Whittle software.

This is only useful to those who have not used Whittle previously. This section covers

importing data into Whittle, generating pit shells and ultimate pit limits, designing

pushbacks from pit shells and optimization with the Milawa-NPV option. Some of the

traditional sensitivity analysis, such as varying commodity price and processing capacity

are also included in the notes, but is not necessary for this assignment. You are, however,

encouraged to explore these features if desired.

The data set used in this assignment is generated from an estimation method (ordinary

kriging). The estimated orebody model will be used as input and the resulting schedules

and pushbacks obtained in the first part are referred to as the “base case” during analysis

performed in subsequent assignments.

1 Import Deposit Data in to Whittle

a. Make a new directory in C:\ drive (or the network) called “Assignment 1” Then,

inside the workshop directory, make a subdirectory called “working.”

b. Copy the files: ‘parfile.par’, ‘kriging.mod’ found in the directory

…\Assignment 1\MOD FILES into the “Assignment 1” directory you just

created.

c. Open Whittle and import parfile.par and kriging.mod files as follows:

d. Click on create a new project and press OK.



e. Type project name: Assignment 1, select the project directory by clicking on the

directory icon on the right side—C:\Assignment 1\. Then, select the “working”

directory—C:\ Assignment 1\working. Click on “next”, for import type, choose

“Whittle block model”. Browse the “workshop” folder to find “kriging.mod” as

the model file to import, and “parfile.par” as the parameter file to import. Then,

click on finish and “yes” to confirm. If there are any additional windows that

appear asking for parameters, simply keep selecting “Next” or “Finish” until

they go away.



f. Check the parameters loaded and run the program by clicking on the third man

icon . A green check mark should appear beside “New Block Model”.

g. Under “New Block Model”, select the “Description” tab and change the block

model’s description from “New Block Model” to “Kriged Model”.

h. Under the “Formats” tab, set the “Units” for Element A to “tonne”. Not setting

the correct units in Whittle can lead to misleading results.

i. Press the “Accept” button to accept the changes.

j. Now, click on each of the tabs and check what information is provided.

k. When finished, select the “Check Data” button to ensure that all data has been

correctly entered.

2 Generate Ultimate Pit Limits

a. Click on “New Slope Set” on the left and description tab on the right. Type

“Kriging Slope Set” for the description and click on “Accept” keeping all the

values as default. Click on “Profile” tab and check the parameters to ensure that

the slope angles are correct, as per the assignment requirements (Section 2).

b. Click on “New Pit Shells” on the left and description tab on the right. Type

“Kriging Pit Shells” for the description. You will need to enter all of the

parameters defined in Section 2 into the appropriate tabs. In particular (and for

future steps with similar options), it is beneficial to use the following parameters

(below). Once again, it is important be mindful of your units (% recovery,

grades expressed as decimals, pounds for selling on market, etc.) When

finished, press “Accept”.



c. Right-click on “New Schedule Graph” on the left side and choose “Cut Branch”

from the menu. Repeat for the “Pit by Pit Graph” node.

d. Click on description tab and type “Operational Scenario-1.” Click on “time

cost” tab and change the discount rate. Then, Click on the “limits” tab on the

right side and change the value of the mining and processing limits.

Additionally, ensure that the units for “Element limits” is set to pounds. Then,

click on “accept”.

e. Add Pit by Pit Graph: Right click on “Operational Scenario-1” and add “Pit by

Pit Graph”. Click on “description” tab and type “Pit by Pit Graph-1”. On

schedule tab, ensure that “fixed lead” is selected with “0” value. In the

“Definition” tab, delete all the lines below “tonnage of waste rock”. Then add a

new value to be displayed by clicking in ‘add’ select “Output” on the left and

select “Undiscounted revenue and cash flow” on the right, and choose “Open Pit

Value”. In order to generate various graphs (as outlined in the assignment

deliverables), you will need to repeat this step and select the correct properties

to save. You will likely need to explore the various options to be able to get the



correct graphs. Do not hesitate to include a new graph not outlined in the

assignment deliverables if you believe it helps you justify your points in your

report’s discussion. Click on add to selection list and best case, click on OK.

Then, click on OK and accept it by clicking “accept” in the general window.

Then, run the program by clicking the running man icon.



f. Generating the pit list: Right click on the Kriging Pit Shells and select “Other”-

“Export Pit List”. Select the assignment 1 directory and change the name to



kriga.pil, click on run. Click on “OK” for the message. You will need these pit

shells for future assignments.



g. Finding the optimal pit: Click on “Pit by Pit Graph-1.” Click on “output” tab

on the right side. It shows the best, specified and worst case scenarios. The

optimum pit can be found from there (checking in the discounted cash flow it

may be seen which pit shell has the highest value and therefore may be chosen

as the ultimate pit).



h. Click on the “Graph” tab and press zoom button. Click on the preferences. Type

DCF on the Title of Y-Axis. Select only “Open Pit Value” and unselect the

other options. Click on the 2nd

Y-Axis preference tab and unselect “Use multiple

Y-Axis” because you have chosen only one display (there is no need to display

the 2nd

axis). Click on “Style preferences” and select “Open pit value for the

best case.” Change the Style to Bar, and Colour to red. Click on Graph tab to

see the modified plot. Repeat these steps to generate your graphs required for

the assignment deliverables. Be sure to comment on your results.



3 Generating Pushbacks from Pit Shells

a. We will first create pushbacks using the automatic pushback selection tool.

Right-click on “Pit by Pit Graph-1”, and select “Copy Node”. Right-click on

“Operational Scenario-1” and select “Paste”. Change the name of the node

(“Description”) and re-name it to “Pit by Pit Graph-#” where # is the number of

pushbacks you wish to test. Under the “Schedule” tab, and under “Specified

case pushback definitions”, select “Auto” and enter the number of pushbacks

you would like in your design. Select the “Definition” tab, and press “Edit”.

You can now enter the final ultimate pit shell to be considered (the limit of

mining); enter the ultimate pit shell number defined in Step 2 (g,h) in the “End”

textbox. You will not need to worry about the graphs in this step, as they will be

generated in more detail in the following step. Press the running man icon to run

the pushback designs. After the algorithm has finished running, under the

“Schedule” tab, you will see numbers listed in order beside “Pushbacks used for

last run”. These tell you the optimal pit shell combinations that Whittle has

chosen, given the number of pushbacks you have selected. You will need to

remember where to find these numbers, as they will be required in the following

step (Step 3 b). Repeat this step for various numbers of pushbacks by copying

the node and pasting under “Operational Scenario-1”, and changing the number

of pushbacks.

b. Adding Mining Width (combine pit shells to pushbacks): Right-click on

“Kriging Pit Shells” select “Add” and “Mining Width”, then, click on the

“Description” tab and type “Kriging Mining Width - # Pushbacks” (where # is

the number of pushbacks you want to consider). Click on the “Definition” tab

and type in the desired mining width (justify your parameters in your report). If

you are unsure of any of the parameters in this menu, please refer to the help file

in Whittle. Then, in “Pushback definition”, click on edit pushbacks and type in

the desired pit shells numbers to be considered as pushbacks. These were made

available to you in Step 3 (a) under “Pushbacks used for last run”. Run the

program to combine pit shells to pushbacks. You will need to repeat this step for

each pushback configuration you wish to test (# of pushbacks in design). It is

recommended that you save these as new scenarios



c. Right click on your pushback scenario created in the previous step (Kriging

Mining Width - # Pushbacks), and select “Add” then “New Operational

Scenario”. Whittle should add the correct parameters, however if they are

incorrect, be sure to put in the correct parameters, as per Step 2 (d). Right click

on your new operational select and select “Add” then “Pit by Pit Graph”. Under

the “Schedule” tab, ensure that “Specified Case Pushback Definitions” is set to



“Manual”, and you will need to add your pushbacks. Press the “Add” button,

and then enter your pushbacks in increasing order (e.g. if you have 4 pushbacks,

you would enter “1 2 3 4”). Press “OK”. Under the “Definition” tab, ensure that

Whittle will generate the correct graphs that you require. When ready, press the

running man button. Under the “Graphs” tab, you should now be able to see

your graphs for the pushbacks (i.e. not pit shells, as shown in the previous step).

You will need to re-do this analysis according to the various # of pushback

scenarios you have chosen. Compare what happens in pushback tonnages, ore

tonnages, etc. to justify your decision on number of pushbacks in your design

before going on to the next step.

d. Generating Pit list Krigb.pil: Right click on “Kriging Mining Width”, tools-

exporting pit-list- select the working directory and change the name to krigb.pil,

export it. Here, this pit list contains block coordinates and the number

representing three pushbacks. You will need to do this for which ever design (#

of pushbacks) you deem best. The output file is required for future

assignments.



4 Optimization with Milawa-NPV

a. New Schedule Graph: Create a production schedule by right clicking on the new

operational scenario (whichever was deemed optimal from the previous step),

selecting “Add” then “Schedule Graph”. In the “Description” tab, type “Kriging

Schedule – Milawa NPV”. On “Schedule” tab, click on “Milawa NPV” and

click on “add” on the right side, pit 1, then pit 2 and pit 3 by clicking “add” on

the right side(Add as many pits as needed). Select “Milawa NPV” as the

“Specified case scheduling algorithm”. On definition tab, delete all the lines

below “tonnage of waste rock” and click on add. Then, click on “output” on the

left, and on the right choose “element and grade” and at down choose “Qty of

<element> output from <method> (<method><element> /UO*) to have metal in

the output file. Click on “add to selection”, choose “Cu”, from “mill” for

“specified case”, and OK. Click “accept”. Feel free to add whatever graphs

necessary to justify your decisions in your report’s discussion. Then, run the

program by clicking on 2nd

running man. Repeat this step for “Milawa

Balanced”. Discuss the differences between the output schedules, which one

you think is more effective, etc.

5 Exporting the Results to an Excel Worksheet

a. Right-click on the menu-button on the optimal pushback design you have

chosen on the left side. Choose “Options” then “Export Files” options. See that

the directory file will be created (directory can be changed by clicking at the

end of directory name box). Click on the square beside “Spreadsheet File” to

put a check-sign and type the name as “krigpb.csv” and Ok .

Gu a Whittle

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