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Drill & blast management
Interconnected mine scheduling
Reliable proximity awareness underground
Dynamic survey surface updates
3D mine planning & geological modelling
Streamlined geological modelling workflow
Machine learning assisted domain modelling
Material tracking & reconciliation systems
3D laser scanning & imaging
Point cloud processing & analysis
LiDAR-based stability & convergence monitoring
Derive value from airborne or mobile sensor data
One of the key issues when it comes to strategic planning for a mining resource is that investment expense is often left out of the process. Combined with the fact that deposits today are more complex (i.e. polymetallic deposits), and marginal, due to the reduction in ore quality and increase in depth, it has become more relevant to dynamically analyse the capital decisions influencing project feasibility.
Strategic optimisation programs often do not incorporate capital investments as part of the process. Strategically, it is important to analyse different plant capacities and configurations, truck purchase policies and infrastructure requirements dynamically – that is during optimisation – to evaluate the mining project in its real world context. This is particularly important when working with multiple deposits.
Maptek scheduling solution Evolution optimises cutoff grades for multiple elements and processes, as well as the extraction sequence looking for the best Net Present Value. From version 6, Evolution allows users to dynamically incorporate the analysis of capital decisions as part of the optimisation. This means users will be able to obtain a more robust analysis of the cutoff grade policies and extraction sequence based on capital expenditure.
Evolution Strategy is fundamentally based on evolutionary algorithms, however, for certain subsets of problems it uses classical techniques, such as integer programming. The use of evolutionary algorithms provides a flexible and powerful environment to solve problems with extensive and non-linear search spaces, where other methods are not able to find solutions in a reasonable time.
This type of algorithm allows multiple policies to be optimised globally in a very efficient way. The ability to simultaneously optimise strategic capital decisions as well as multiple mining policies (cutoff grade, mill capacities, trucks, stockpiles etc.) across multiple mine sites greatly reduces the iterative process involved in global optimisation.
Another important aspect of Evolution Strategy is the ability to directly use block models, which allows users to reduce data manipulation, minimising the risk associated with this task, and focus on the search for solutions that add value to their mining project.
This new block model approach in Evolution Strategy provides the opportunity to evaluate capital investments more robustly, making it a very attractive option for users.
Eduardo Coloma
Chief Executive Officer
September 5, 2019
For additional information about Maptek, including use of the Maptek logo, product images and reproduction of case studies, please direct inquiries to Global Marketing Communications Manager jane.ball@maptek.com.au
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