Micromine 2016 offers new scheduling workflows, that have been developed for ease of use and simplicity at the point of design allowing users to take advantage of the intuitive tools to create and prepare mine plans.
These days powerful scheduling tools are known for their notoriously high price tags and steep learning curves. However, Micromine has sought to address these problems with the release of the enhanced features within the scheduling module in Micromine 2016.
With the release of Micromine 2016, the development team included key features to the Scheduling module, incorporating a new and enhanced Schedule Optimiser that provides engineers with the means of identifying an optimal mine plan. The Schedule Optimiser is a driven mathematically proven Mixed Integer Linear Programming (MILP) solver, that identifies an optimal extraction sequence.
The optimisation process is based on a concept of maximizing an objective, for example ore or metal tonnes. Micromine converts the mining problem into an optimisation model that can be optimised by the MILP solver.
The highly intuitive and simple workflow is based on using 3D solid wireframes. Solids are interrogated against a block model while calculated material quantities and qualities are simultaneously written onto the wireframes as attributes. The wireframes are subsequently imported into scheduling so they can be sequenced and optimised.Micromine 2016 provides a number of new and dedicated tools for each major component in the process. The new create mining block tool has been specifically designed to use input design solids to quickly create task wireframes. The enhanced grade tonnage reporting tool now allows users to define and report on a number of material types. The scheduler provides dedicated functionality embedded into different project types for life of mine and short term schedulers. The philosophy is to prepare data to generate an optimised life of mine solution and subsequently use the solution as the base for a more detailed mine plan.
Micromine’s new long term scheduler can take any number of inputs as variables and an optimization objective, for example metal tonnes, then aims to find an optimal solution out of multiple, potentially millions of possible outcomes. The objective attribute is discounted over time, as the optimiser endeavours to extract blocks as soon as possible to maximise discounted Net Present Value (NPV).
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