Optimizing Truck Loadout and Mine Traffic Management

Optimizing Truck Loadout and Mine Traffic Management

Problem:

A leading exporter of coal wanted to ensure their new truck loadout facility could meet current and future demand. Static tools like Excel weren’t enough to account for the real-world complexity of mine traffic management and system interdependencies.

Solution:

The consulting team built a dynamic simulation model in AnyLogic to test layout options, operational policies, and "what-if" scenarios. This simulation-first approach enabled faster decisions and supported early-stage mining optimization.

Results:

  • Tested thousands of layouts and scheduling scenarios.
  • Identified the ideal number of weighbridges and tarpaulin stations.
  • Optimized bin sizes for steady truck flow.
  • Planned around train schedules to prevent disruption.
  • Prevented bottlenecks and costly infrastructure rework.

Introduction: a smarter start to mining optimization

When one of the world’s leading coal exporters wanted to validate the design of a new truck loadout facility, they turned to simulation. To help them do it accurately and efficiently, the company partnered with Jaco-Ben Consulting, a consulting company known for its expertise in industrial operations and simulation modeling.

The client needed to make confident infrastructure decisions before construction began. The team used AnyLogic to build a data-driven simulation model, giving stakeholders a clear way to explore design options, test assumptions, and avoid costly missteps.

Problem: avoiding costly mistakes before construction

The client was preparing to build a new truck loadout facility at one of their coal plants, but before beginning, they wanted to be sure the design could handle both current and future demand. Their primary concern was how design decisions would impact mine traffic management in both stable and high-volume scenarios.

At first, the process looked simple: trucks arrive, get weighed, get loaded, and leave. But in practice, the system was full of moving parts and interdependencies that made it hard to predict performance using static tools like Excel.

A site layout map illustrating the sequential process flow for truck loading and weighing operations

Overview of loadout layout for mining facility optimization (click to enlarge)

The consultants needed clear answers to questions like:

Even small changes in layout or scheduling could create bottlenecks. And the cost of redesigning infrastructure after construction would be high. The consultants needed a way to test different configurations, understand trade-offs, and simulate real-world variability—all before anything was built.

Looking to optimize mining operations? Check out our case studies to see how companies around the world are already doing it with AnyLogic software.

Solution: using simulation to improve mine traffic management

To resolve the complexity of the loadout facility design, the consulting team turned to AnyLogic. Simulation would give them a low-cost, low-risk way to test layout decisions, operational policies, and “what-if” scenarios, long before anything was built.

The consultants used AnyLogic’s Process Modeling Library to quickly build a visual, flowchart-style model of the facility. This helped both technical and non-technical stakeholders understand what was happening in the system.

The model was simple, but powerful enough to support detailed mining optimization across key stations: weighbridges, silos, reclaimers, loading areas, and more.

AnyLogic Cloud simulation model for mining optimization and traffic flow

AnyLogic simulation for mining optimization and traffic flow (click to enlarge)

One of the biggest strengths of using AnyLogic was its flexibility. Since it’s Java-based, the consultants could integrate it with standard Java libraries for tasks like unit testing, automated scenario generation, and exporting results. This made it easy to verify model logic, implement quick changes, and ensure everything worked as expected.

Simulation model in AnyLogic Cloud for mine traffic management

Simulation model for mine traffic management (click to enlarge)

They created two main modes in the model:

AnyLogic Cloud model of sensitivity analysis for the truck loadout station simulation

Sensitivity analysis for the truck loadout station simulation (click to enlarge)

All scenarios were data-driven and loaded from Excel files. That allowed the consultants to tweak inputs, replicating real-world variability easily. They could also explore system behavior under different conditions, like what happens when train loading overlaps with truck operations.

This ability to test real-world conditions was critical to improving mine traffic management and ensuring scalable mining optimization.

In the end, the model didn’t just show how the facility would operate. It helped the client test design ideas, avoid bottlenecks, and confidently make smarter infrastructure choices.

Results: clear answers that saved both time and costs

The simulation gave the client a clear view of how their design choices would play out before anything was built. The most valuable insights came from the sensitivity analysis experiment, where the team tested thousands of scenarios and parameter combinations.

They were able to see how truck cycle times changed based on:

A line graph illustrating the relationship between average truck cycle times and facility output for different bin sizes

Average truck cycle times vs bin size, with 1 export train a day

A line graph illustrating average truck cycle times by area versus facility output

Average truck cycle times vs number of tarpaulin covering stations,
with 3 weigh bridges in and 3 weigh bridges out

A line graph illustrating average truck cycle times versus facility output at a 2250tph feed rate, comparing different bin sizes

Average truck cycle times at 2250tph feed-rate

These results directly influenced design decisions. For example, the analysis illustrated that just one or two tarpaulin stations would cause major delays, while three or more kept operations stable. It also helped the client understand how smaller bin sizes would affect throughput, and how train events could be scheduled to avoid disrupting truck flow.

In the end, the model helped the client avoid costly missteps, optimize the layout early, and plan for future demand—all backed by real data.

The case study was presented by Jaco-Ben Vosloo and Devon Cowling from Jaco-Ben Consulting at the AnyLogic Conference 2024.

The slides are available as a PDF.


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