A comprehensive study was carried out at one of South Africa’s largest open-cast coal strip mines, where haul distances vary between 0.8 and 3.5 kilometers. The operation relies on a truck–shovel–conveyor system, and mine management sought to apply simulation modeling to enhance fleet planning and evaluate buffering strategies at the conveyor intake for improved efficiency and throughput.
Challenge
Determine whether a buffer stockpile is needed in front of the conveyor—and, if so, define its optimal size
Identify the minimum number of trucks, dozers, and excavators required to reliably meet production targets after the mine’s expansion
Evaluate plan fulfillment rates under real-world equipment availability constraints
Objective
The study was initiated to answer several interdependent planning questions:
Buffering: Is a stockpile required in front of the conveyor system? If so, what should its optimal capacity be?
Fleet Sizing:
- How many trucks are needed to meet the plan?
- How many dozers are required to maintain dumping and cleanup operations?
- What is the minimum number of excavators required to consistently hit daily targets?
All scenarios were evaluated under 95% equipment availability, reflecting real-world maintenance and reliability expectations.
Solution
MineTwin was used to build a detailed digital model of the mine’s production cycle, including:
- Realistic replication of mining sequences, haul distances (0.8–3.5 km), and equipment cycle times
- Simulation of operations with and without intermediate stockpiles
- Scenario testing to evaluate multiple fleet configurations
Stockpile Buffering Impact
Introducing a 10 kt buffer ahead of the conveyor significantly reduced system delays and allowed for smoother operation, especially under fluctuating haul cycle times.
Fleet Optimization
MineTwin identified right-sized fleets that could meet production targets with minimal redundancy:
- Overestimating fleet size did not proportionally improve throughput.
- Undersized fleets quickly led to plan shortfalls, even with high availability.
- Determined that additional 7 dozers and 6 trucks will be required to sustain the operations after the mine’s extension.
Why MineTwin
MineTwin is purpose-built for mining. Unlike generic simulation or planning tools, MineTwin is designed specifically to replicate the operational realities of both open-pit and underground mines. It models detailed interactions between equipment, including truck–shovel coordination, queuing delays, and haulage cycles. This level of specificity allows it to capture non-linear constraints and cyclical dependencies that are typically overlooked by spreadsheets or linear programming models.
MineTwin bridges strategy and execution. Its simulation-based approach allows planners to test the feasibility of mine plans under realistic conditions, accounting for equipment availability, geological uncertainty, and process interdependencies. This makes it an effective link between high-level mine planning and on-the-ground operational decisions.
MineTwin is scalable, configurable, and in-house friendly. MineTwin enables mining companies to build internal competence centers that support multiple sites with a single modeling platform. It is flexible enough to adapt to different mine layouts, workflows, and business rules. Once deployed, MineTwin empowers mine planners to independently run scenario analyses, optimize fleet configurations, and evaluate operational changes—supporting continuous improvement and better investment decisions.
Benefits
Simulation confirmed that a 10 kt ex-pit stockpile improves operational stability and reduces the probability of plan shortfall by 90%.
The model identified optimal fleet sizes needed to achieve high fulfillment rates under constrained availability.
It was determined that an additional 7 dozers and 6 trucks will be needed to sustain operations after the mine’s extension.
Download a PDF of this case study: MineTwin Coal Mine Case Study
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