Haul fleets matched to the pit, hour by hour
Truck-shovel assignment drifts from optimal as faces, grades, and availability change. Dispatch models re-solve against the pit as it actually is.
Every tonne moved for a reason.
Fleet dispatch, blending, and mine-to-port planning built as optimisation problems. The decisions that set your cost per tonne are made hourly, and they should be made with a model.
Three problems worth modelling
Blends that hit spec without giving away grade
Stockpile and blending decisions routinely over-deliver on quality to stay safe. Optimisation holds spec at the lowest grade give-away the constraints allow.
The chain from face to vessel, planned as one
Pit, crusher, stockpile, rail, and port are usually planned separately and reconciled by expediting. Modelled together, the real constraint becomes visible.
What we build
- Truck-shovel dispatch and fleet allocation under changing face availability
- Short- and medium-term mine scheduling against grade and capacity constraints
- Blend optimisation across stockpiles to hold product spec at minimum give-away
- Rail and port logistics planning, including cycle times and berth windows
- Equipment failure prediction on haul trucks, shovels, and fixed plant
- Scenario planning for grade variability, equipment loss, and demand shifts
Methods: MILP, network flows, stochastic optimisation, discrete-event simulation
Outcomes
- Lower cost per tonne: fewer empty and mismatched haul cycles
- Less grade give-away: blends that meet spec rather than beat it
- Fewer surprises: the binding constraint identified before it stops the chain