Model mining operation simulation that matches reality
Simulate haul cycles, underground routing, fuel and battery performance
GNOS removes guesswork from mine planning by delivering a precise, data-driven simulation platform. It integrates haulage, energy, and cost modelling in a single environment to replicate real operational conditions. The platform translates every operational change into specific, quantitative metrics, giving clear evidence of cost, efficiency, and environmental impact differences.
Our platform models vehicle and route dynamics far beyond fixed-time or simple event approximations to reveal actual haul cycle variability under varying payloads, gradients, and network congestion. Teams evaluate fleet adjustments, route layouts, and technology transitions using measurable operational data.
GNOS simulates longitudinal traction forces for haul trucks, shovels, and conveyors. It captures regenerative braking to enable energy recovery on downgrades. Our terrain-responsive model adjusts vehicle speed and fuel or battery consumption based on grade steepness, surface roughness, and weather-affected adhesion changes, including seasonal variations such as rain, dust, and snow.
01
02
03
Rapid testing for blast sequencing and operational changes
Short-term changes such as blast sequencing, unplanned grade targets, or weather-related route shifts create operational uncertainty.
GNOS enables rapid scenario testing to evaluate how these changes affect cycle times, fleet allocation, and production targets. Planners can model new blast zones, altered haul routes, or revised dispatch priorities within minutes, identifying the most efficient operational response before implementing changes on site.
Fleet expansion and route alternatives
Advanced dispatch and blending optimisation algorithms automatically balance grade targets, equipment availability, and cycle times, to model operational variability and ensure consistent output quality while maximising utilisation.
For underground load and haul GNOS’s model continuously reserves route segments and dynamically reroutes vehicles in response to current network conditions, mimicking how dispatchers and drivers operate in practice. While operators can avoid deadlocks and conflicts intuitively and via radio communication, most simulators cannot replicate this coordination accurately. Our algorithms automatically balance grade targets, equipment availability, and cycle times to model operational variability and ensure consistent output quality.
Add or reconfigure trucks, loaders, and excavators to measure marginal output.
Test new haul circuits or underground headings before construction.
Evaluate infrastructure changes such as passing bays, road geometry, or dual‑lane sections.
Maximise fleet utilisation without risking unrealistic blocking or deadlocks in the simulation.
Stress‑test mine networks under variable operating conditions
Maintenance events and infrastructure failures can trigger cascading impacts across the mine. GNOS lets you simulate major shutdowns, minor outages, and overlapping resource constraints to reveal their true effect on production. The platform identifies how equipment downtime shifts queues, causes bottlenecks, and alters loader, excavator, and truck utilisation site-wide. Run targeted scenarios to test alternative recovery strategies, staggered maintenance windows, or reallocation of assets to enable precision scheduling and realistic contingency planning.
Simulate road washouts, weather events, or unplanned equipment downtime.
Identify weak points and evaluate rerouting and recovery strategies.
Quantify production and haulage throughput impacts under each scenario.
Maintenance scheduling and fleet resilience
Planned and unplanned maintenance events disrupt haul cycles, reducing fleet availability and throughput. GNOS models maintenance schedules, equipment downtime, and partial fleet operation to quantify production loss and recovery time. Planners can test alternate maintenance windows, evaluate backup equipment strategies, and assess the operational cost of extended service intervals. The simulation reveals how staggered maintenance schedules minimise throughput impacts while maintaining asset reliability.
See your haul network modelled with full physics.
GNOS runs complex mining scenarios side by side. Teams can run dozens of operational variations at once to evaluate operational, fleet, and energy changes in parallel to understand production impact and cost before making physical adjustments.
Engineering accuracy in every cycle
GNOS models mine operations with the same engineering precision used in heavy transport systems. It captures each load, haul, and dump cycle in full motion. The simulation integrates traction, grade resistance, power curves, and energy draw across mixed fleets. Every output aligns with field‑recorded results, showing how truck interactions, loader cycles, and terrain affect production.
Real haul cycle behaviour
Most mining simulations treat haulage time as a fixed or simplified event, which overlooks key operational realities. GNOScalculates vehicle movements in continuous motion, capturing how actual haul trucks, shovels, and conveyors behave in real time.
The GNOS platform models detailed traction forces, including gradients, curvature, tyre adhesion, and weather effects such as rain or dust. It can simulate how wet or dusty conditions alter traction and fuel use, providing insights into seasonal adhesion variations. Teams can then better understand how environmental factors influence cycle time, queuing, and idle delays.
Detailed insights allow operations to optimise routing, equipment placement, and cycle sequencing to minimise delays and maximise throughput. By accurately modelling the full load–haul–dump cycle, GNOS identifies zones where queuing occurs, how idle periods extend cycle times, and where under‑utilised assets reduce efficiency.
GNOS executes multiple scenarios at once. Users can test new routes, extended fleets, or energy transitions simultaneously. Each simulation returns measurable results on productivity, energy use, and carbon impact.
Integrated planning environment
Full supply chain visibility from pit to port
GNOS extends mine simulation to model material flow from extraction through stockpiles, crushing plants, rail loadouts, and port terminals. The platform identifies bottlenecks across the entire supply chain, revealing how delays at any stage cascade through operations. Teams can test stockpile sizing, conveyor capacity, train scheduling, and port loading strategies within one integrated model, ensuring on-time delivery and optimal material flow from pit to port.
Surface and underground in one model
GNOS models surface and underground networks within a single simulation environment to prevent gridlocks and facilitate smooth traffic flow in constrained environments. Operators coordinate via radio or control, navigating using continuous routing instead of relying on rigid traffic events. GNOS’s advanced GNOS algorithms enable vehicles to find realistic, deadlock-free paths even in complex underground mining networks where most competitors fall short.
Energy modelling and emission planning
Plan decarbonisation with realistic fleet behaviour
Test charging layouts, grid capacity, and battery swap options.
Identify weak points and evaluate rerouting and recovery strategies.
Model stepwise fleet conversion, energy demand, and carbon intensity over time.
In-built AI assistance for onboarding and training
GNOS includes an integrated AI assistant that simplifies setup, operation, and learning. It guides users through model creation, highlights configuration issues, and recommends optimisations based on similar simulations.
Guided setup
In‑platform learning
Continuous improvement
Surface and underground in one model
Compare baseline production with planned expansions or new
haul routes.
Measure impacts of delays, breakdowns, or seasonal variation through distributed compute.
Export dashboards comparing throughput, energy use, and
cost outcomes.
