4.1 Evaluating the Autonomous Haulage Business Case

Assessing the business case for adopting autonomous haulage in underground mining requires a comprehensive analysis of both the financial and operational impacts. The decision should be driven by a balance of upfront costs, long-term savings, operational efficiencies, and risk mitigation. Here are the key factors to consider when evaluating the business case for autonomous haulage:

4.1.1 Initial Capital Investment

• Autonomous Vehicles and Infrastructure:
  • The purchase of autonomous trucks, along with the necessary infrastructure upgrades (e.g., communication networks, charging stations for electric vehicles), represents a significant capital expenditure. Mines must evaluate the cost of acquiring autonomous equipment versus maintaining or upgrading their current manual or semi-autonomous systems.
• Software and System Integration:
  • Integrating autonomous vehicles with existing mine management, dispatch, and fleet systems can also require substantial upfront costs. Software customization, data infrastructure upgrades, and control room setup may be needed to support real-time vehicle monitoring and control.
• Cost Comparison:
  • Compare the upfront capital investment of autonomous systems with alternatives, such as manual haulage, semi-autonomous vehicles, or fixed material handling systems (e.g., conveyors). Evaluate which option provides the best cost-benefit balance for the mine's current and future needs.

4.1.2 Operational Cost Savings (OPEX)

• Labor Cost Reduction:
  • One of the most significant advantages of autonomous haulage is the reduction in labor costs. Autonomous systems reduce the need for drivers, allowing mines to lower wages, recruitment costs, and expenses associated with managing shift changes and labor shortages. However, there may be increased costs for upskilling and retaining technical staff to monitor and maintain the autonomous fleet.
• Fuel and Energy Efficiency:
  • Autonomous vehicles often operate more efficiently than human drivers, optimizing fuel consumption or electricity use. Electric autonomous vehicles, in particular, can reduce fuel costs and decrease the mine’s carbon footprint. Mines need to evaluate how much they can save on fuel or energy compared to their current fleet.
• Maintenance and Downtime:
  • Autonomous vehicles can also reduce maintenance costs through optimized driving patterns that minimize wear and tear on equipment. Predictive maintenance systems that are integrated with autonomous trucks can anticipate repairs before they become critical, reducing downtime and extending vehicle life. Mines should calculate potential savings from lower maintenance and reduced equipment replacement costs.

4.1.3 Productivity and Efficiency Gains

• Continuous Operation:
  • Autonomous haulage systems offer the advantage of 24/7 operation without the need for shift changes, rest breaks, or human-related delays. This can significantly increase productivity by moving more material over longer periods. Mines should quantify the potential increase in material moved per day or year, and how this impacts overall revenue.
• Optimized Haulage Routes:
  • Autonomous vehicles are programmed to follow optimized routes, minimizing travel time and improving cycle efficiency. This leads to faster material transport and reduced idling time, further increasing operational efficiency.
• Cycle Time Reduction:
  • By eliminating variability introduced by human operators, autonomous trucks maintain consistent speed, acceleration, and deceleration, reducing cycle times and improving throughput. Mines need to assess how much cycle time reduction will translate into operational gains.