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4 SIMULATION MODELS
Dedicated simulation packages need specialists to
run and interpret the results, usually with cost and
licensing restrictions. They represent a barrier to
practitioners who must learn a new package if they
are to run the models independently.
Developing the system in Excel
TM
allowed
mining engineers and operators to explore
alternative policies and scenarios, using domain
knowledge unavailable to the designer of the
simulation model. Graphing and analysing of results
was built in, so minimal ongoing assistance was
required from the simulation provider.
Constructing a simulation model in a spreadsheet
workbook, run by VBA macros, is as easy as in a
dedicated simulation package. The spreadsheet’s
data input and output reporting and graphing
capabilities are fuller than are generally found in a
simulation package. The industry user, familiar with
spreadsheets and their potential, can suggest
improvements to the simulation model. The VBA
macro coding is hidden from the practitioner, who
can use it by means of inbuilt buttons and menus.
The simulation model comprised three VBA
macros: reading in parameters to set up the
simulation; running the simulation the required
number of time periods, and finally using Excel’s
statistical and graphing power to report the results.
The models were used to study the effects of
controllable variables (such as stockpile sizes and
stockpiling methods) and uncontrollable variables
(such as cargo sizes). The worksheets specified
parameters and policy choices, displayed simulation
progress, and reported and graphed a performance
summary for any simulation run. For reproducible
results, a year or more of production had to be
simulated.
The simulation was time-sliced (at six hour
intervals) rather than event-driven. In each time
interval, ore is mined and trains loaded, while at the
port trains arrive and are unloaded, crushed and
stacked to stockpiles, ships can arrive, commence
being loaded from an available stockpile (or wait if
none are available) continue being loaded, and
depart when full. Simulations were run to explore
the effect of steadily changing the values of a
particular parameter, or a set of parameters.
Separate workbook models were written to
simulate the Mine and Port operations. They could
be run individually, or be run together by a Master
model, for a sequence of scenarios. Space limitation
limits discussion here to the Port model.
5 PORT MODEL EXAMPLE
The Port model has six worksheets, simulating stack
and reclaim of ore from train to ship.
The “Input Rakes” sheet imports a set of 2,048
train rakes from the “Output” sheet of the Mine
model file. Incoming trains are from either of two
pits that have systematically different mean grade, to
reflect planned trends in mining.
Figure 2 shows the Port “Specify” sheet. Settable
parameters are in yellow cells. In the example, the
ore arrives at 40 million tonnes per year, with a train
every six hours (generated in the Mine model). This
model explores a plan of up to four ship berths, with
each berth fed from a stockpile of nominated
capacity. Stockpiles can be fully Blended in Blended
Out (BIBO) or built First In First Out (FIFO).
Stockpile sizes are here set 240kt and 360kt. Train
and ship arrivals be equally spaced or random. The
cargo capacities distribution is specified. Each
incoming train can be direct loaded (with chosen
probability) to a ship, or sent to a stockpile, chosen
by a weighted composite of four criteria.
A “Progress” worksheet allows the system to be
tracked, at a chosen multiple of 6 hours, for a chosen
time range. This is useful for debugging, and also for
better understanding the system behaviour.
For each mineral, the “Cargoes” worksheet
graphs the cargo compositions varying around
target. For example, Figure 2 shows that the
“Process Capability” (the Tolerance divided by
twice the Standard Deviation) for Fe is 1.15.
The “Audit” worksheet reports the full simulation
history, with product flows and stockpile and ship
berth states for each time interval. Tonnage aspects
of the simulation history are plotted to aid
interpretation, and validate the parameter values
selected on a particular run.
58.0
58.2
58.4
58.6
58.8
59.0
0 120 240
+/- Ship Tolerance
95% Confidence
Days
Fe Cargoes
Process Capability=1.15 (2% Out of Tolerance)
Figure 2: The “Cargoes” Report.
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