Pit Optimisation is used to determine the most profitable open pit, given a mineral resource and a set of economic and metallurgical parameters. It is also used to analyse stockpiles and costs over time.
Pit Optimisation is fully integrated with Micromine. There is no need to manually import and export files to exchange data with other applications.
Micromine Core is mandatory for all Micromine modules.
What is Pit Optimisation?
Pit Optimisation uses the industry-standard Lerchs-Grossman (LG) algorithm. Given an ore deposit represented as a block model containing ore grades or block revenues, the LG algorithm determines the pit shape by identifying the overlying blocks that must be removed to provide access to each block within the block model.
The first outcome of pit optimisation is to determine the ultimate pit that gives the highest possible undiscounted surplus between net revenue and total operating costs, without considering scheduling constraints or discounting.
A nested pit shell analysis is then used to determine the discounted optimal pit. Nested pit shells are a sequence of ultimate pits generated by incrementing the commodity price across a range of values around the base price. The optimal pit gives the highest possible net present value, taking into account all operational scheduling constraints (annual mining and processing productivity), discounting and recurring capital costs.
- A single workflow-oriented dialog where all parameters are specified and stored as a Micromine form set
- Internal and external (32- or 64-bit) optimiser engines
- Cut-off and cash flow ore selection methods
- Optimisation and Analysis modes
- Support for orebody models without waste blocks, as well as full model type, 3D-rotated, factored or sub-blocked models
- Custom optimisation area to keep pit shells within or outside a polygonal area
- Defining input parameters as functions instead of constants
- Multiple rock types with multiple grades (elements) per rock type
- Multiple processing method groups
- Calculation of theoretical cut-off grades
- Support for multiple slope regions defined by domain directions or wireframes
- Optional support for using air blocks to produce a more accurate pit shell in complex topography
- Variable dilution, recovery and rehabilitation costs
- Optional block size multiplier to minimise processing time for a preliminary optimisation
- Best case, worst case and constant lag analysis
- Incorporation of periodic capital expenses
- Enhanced block model reporting
- Support for minimum pit base or pit shell dimensions to guarantee sufficient working space at the bottom of the optimal pit and exclude undersized pits
- Pit shell output as smooth DTM (digital terrain model), exact DTM or 3D points file
- Parameter and audit reporting with Excel output
- Keeps the job integrated into one application and eliminates the data exchange step needed with most competing optimisers
- Internal and external 32- or 64-bit engines provide the flexibility to adjust the optimiser to suit the available computing resources
- From data to model may be up to four times faster than competing applications
- Widely regarded as being intuitive and easy to use
- Supports any combination of sub-blocked and rotated models and DTM surfaces
- Input parameters for mining costs and element prices can optionally be set up as functions instead of constants, adding greater flexibility to the optimisation process