Mining Case
Study
Applying Analytical
Techniques
Mining
Context Information and Objectives Questions
• This exercise relates to “open-pit” (or “open-cast”) mining – a surface mining technique (in
the open air) performed using heavy-duty mobile equipment to extract valuable mineral ore
for later beneficiation and sale.
• Effective and profitable open-pit mining revolves around the efficient use of costly
equipment to perform a drill and blast process, and subsequently a load and haul process.
• Equipment is costly both from a capital and operational expenditure perspective.
• Mines often have a costly overhead component and rely on large volumes of ore
throughput to operate profitably. Inefficiencies that decrease ore throughput and increase
costs are a challenge that all open-pit mines face.
• Equipment incurs a monthly fixed cost that is independent of the amount of ore extracted
(even if the equipment is not used) as well as a variable cost component arising from fuels,
lubricating agents, maintenance, and other metrics that are related to the use of
equipment.
Open-Pit Mining
Case Study Context
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• In this case study, you are expected to demonstrate some basic analytical capability applied to a mining
case study for an open-pit coal mining operation. Simple key data is provided which you should analyse to
provide any observations or insights you may draw into the operation.
• A CSV file is provided with detailed truck information for a period of one day. This is described in more detail in
the following slides. The Excel spreadsheet provided contains the necessary detail for the summary monthly
mining and financial data for the operation.
• In this case study we will be looking at processing information to assist us in making the appropriate decision
when evaluating how to optimise the trucks (i.e. you are required to process the given information and
provide us with a suggested areas of improvement truck efficiency).
• Firstly, we would like you to review and assess whether there are any trends we can identify from Geospatial
Data over time (such as time spent during activities, sensitivities, ratios / rates, etc.). This table can be found in
the attached Excel file under the “Truck Geospatial Output” tab.
• Secondly, we would like you to process the financial information and identify the reasons for the difference
between budget and actual. Provide suggestions on improving the budgeting process and the benefits of
improving operations (e.g. create three scenarios indicating how your suggestions will improve the financial
position of the mine)
• Lastly, we are looking for slides (in Power Point) to present your findings back to the team (use numbers, charts
and graphs to support your findings). That is, the slides outlining context, charts, graphs, tables; title / agenda
slides can be additional to this.
• Please use Excel for all your analysis and submit the modified Excel file with your Presentation. As a suggestion,
we would recommend for you to use Excel’s pivot and graphing features (and would also benefit from using
the built in Data Analysis toolkits, only if you are already familiar with these). If you qualify, you will be asked to
present your findings and may be asked to perform more analysis using Excel.
Mining Case Study
Objectives
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Geospatial Truck Information
Map
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Note:
HT10-HT13
refer to the
trucks.
• A geospatial truck information transducer which has been installed in each operating truck
is used to provide some basic GPS position and speed data in relation to time to a central
data collection system.
• By defining particular “fences” or “zones” on a map (based on key physical locations such
as the tip and shovels), it is possible to use the GPS and time data to ascertain what action
the truck is performing at a particular time. An example is shown in the preceding slide.
• A “Shovel” is a hydraulic excavator used to extract ore from the ground onto a truck for
transport.
• A single truck cycle generally involves travelling to and waiting for a shovel, being loaded,
travelling to a dumping location, and dumping the ore at the tip.
• The geospatial data for the mine are provided in the included CSV file.
• The granularity of data is provided to one minute intervals, although there are roughly 6
samples per minute. The data also includes a differentiation between night and day shift.
Geospatial Truck Information
Data System
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• You should aim to provide both high level insights into the operation as well as make observations in detailed data.
• How can the granular truck data most easily be understood?
• What can we understand about the trends of the trucks over time?
• Would you make any recommendations around the operations of the trucks?
• How has the operation performed financially compared to what was planned?
• How “efficient” have the costs been?
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Some Guidance
Direction
Mining Case Study
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