Optimised Mine Plans
Ultimate pits are optimised for maximum cash flow, maximum reserve life and maximum NPV.
Easy To Use
Easy to use methodology with multiple layers of sophistication, from quick studies to detailed mine plans.
Sophisticated scheduling, blending, stockpiling, grade optimisation, process optimisation, production targeting and haulage optimisation.
Complete Strategic Mine Planning System
The physical design and the production schedule of a mine are inextricably linked. NPV Scheduler is unique in the mining industry as the only strategic mine planning system that optimises both of these elements in the search for maximum NPV. As a complete strategic open pit mine planning system – NPV Scheduler has functionalities spanning everything from pit optimisation, pushback generation, cut-off grade optimisation, scheduling, haulage optimisation and stockpile management. The advanced system caters for alternative techniques beyond NPV for pit optimisation to take account of material blending requirements or to maximise mine life. The innovative pushback generator delivers the most practical pushbacks of any competing product and the scheduling capability includes optimisation techniques that look ahead to the entire life of the mine as opposed to considering just one period at a time.
Import a geological block model with grade, lithology, topography, surfaces and mining boundaries. Digitise plan data.
Define processing methods and input commodity prices, mining costs, milling costs, selling costs, recoveries and create a three-dimensional economic model with multiple possible 'intrinsic block values' that relate to possible processing methods.
Use the pseudo-flow algorithm to generate a set of nested Lerchs Grossman (LG) pit phases that represent varying economic parameters and generate an Optimal Extraction Sequence (OES) to model the ideal mining sequence. Alternatively, use the options to maximise the life of mine or to generate a blended pit where products are created by mixing rock types.
Use the Optimal Extraction Sequence and pushback ore targets to generate practical pushback shapes that respect good mine design practice.
Schedule the pushbacks according to production targets and mining constraints to get an optimised schedule. Use truck hours and capital costs as inputs. Refine the schedule with blending, cut-off grade optimisation and stockpile scheduling.
NPVS Key Features
Pushbacks are based on LG phases, but practical mining requires careful formation of the final pushback shapes. NPV Scheduler bases the pushbacks on LG phases, bit it also optimises the pushback shapes for practical mining, while retaining the maximum possible NPV.
NPV Scheduler delivers a wide variety of reporting and visualisation options and formats, from full reports with customisable content to 3D rendered life of mine animations.
Easily specify the right truck fleet. Track the tonne-kilometres required to mine the resource and then adjust the schedule over multiple years to minimise peak truck hours and limit the fluctuation in the truck fleet number.
MFO increases NPV by optimising cut-off grade. It adjusts the schedule to create more value by mining higher grade or ore earlier in the schedule when that outweighs the cost of wasting or stockpiling lower grade ore.
Re-allocates the processing of each block (leach pad, mill, stockpile, waste, etc) to optimise multiple blended products (e.g. iron ore) where production targets and product specifications can be blended from different inputs.
A scheduler and material allocation optimiser; it determines the timing of block extraction and destinations for all material types in a block. Scheduling and optimisation proceed period by period, where the 'period' is defined implicitly by production targets; for example, minimum tones to mine.
Multimine Scheduler solves the problem of optimising multiple mines simultaneously to meet shared production objectives. Its flexible scalability makes it applicable to scenarios that range from a cluster of pits at the same site up to a regional mining complex.
GRA manages the uncertainty inherent in interpolating grade distribution by considering conditionally simulated block models in the strategic planning process. It generates a range of risk-rated pits which can be used as the basis for the strategic plan – limiting the impact of grade uncertainty on planning outcomes.
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