// PRODUCT DETAILS

Pit
Optimiser

Gives you access to a powerful cloud-native and feature-rich Pseudoflow solution. Horizontal scalability of cloud compute in the QS Portal allows you to run multiple scenarios in parallel with no impact on your workstation or laptop (in fact, just run it from your iPad if you want to).

Large Models - Multi Output Operation - Optimised Pit Generation

Pit optimisation is foundational to most open pit mine planning processes. Configuring these analyses can be time consuming, particularly if this must be done in another software platform. Execution time can also be slow. If you need to analyse a range of sensitivities, in series, significant time can be consumed.

The Challenge

Our Solution

Unlock the full potential of your mining assets with Pit Optimiser, a powerful tool designed to generate optimised pits for your model using pseudoflow. Experience the efficiency of handling large models seamlessly, utilise a range of inputs for multiple outputs in a single operation, and elevate your strategic decision-making in mining.

Configuration Cloning

Need to run a variant scenario..?? No problem, just clone the configuration, modify, and run.

Large Models

Developed and tested on some of the largest models around, Pit Optimiser in the QS Portal delivers serious power and speed.

User Interaction

With a simple to use interface and intuitive outputs, running and analysing pit optimisation scenarios is rapid and efficient. Genealogy mapping and closed loop validations are built-in, along with plenty of data output optionality.

Best in Class Algorithm

The Pseudoflow algorithm is the current class leading update to the seminal Lerchs Grossmann algorithm.
Pit Optimiser in the QS Portal - the same algorithm, just faster.

Take the first step towards optimising your mining operations! Request a demo of our software and we’ll schedule in a free demo on your data.

Pit Optimisation Demo

Questions?

  • The minimum fields required in the block model are:

    • Geotechnical Domain (a categorical domain such as Lith, Zone, etc)

    • Revenue Field (in $/t)

    • Mining Cost (MCost, in $/t)

    • Processing Cost (PCost, in $/t)

    Geotechnical settings vary by azimuth and geotechnical domain. The Revenue, Mining Cost, and Processing Costs are assumed to be $/t units. The Revenue Factor Range is a provided in a percentage value as an integer (e.g RF 0.5 is entered as 50).

  • A new (Child) block model is cloned and coded for the Revenue Factor pits so that the original block model is unaffected. Multiple pit optimisations can be run off the same block model to create multiple Child Models. The model can be downloaded for ease of use and viewed in the 3D Viewer as required. A pit summary csv is provided as an attachment to the model so there can be no confusion on which model was used to create the outputs.