Challenges

The client was investigating the impact of different automation options on throughput and crew utilization and wanted to use data to justify and drive investment decisions in its autonomous mining strategy across its network of underground mines. The client had specific constraints such as:

• Short-term sequencing of mining tasks, dependent on mining phase, crew requirement per task, and optimal crew allocation.
• Ore storage capacity at bins, different routing of ore to each bin.
• Limited conveyance capacity and limited hoist capacity.
• Planned maintenance activities, and timing of off-shift time, such as lengthy shift changes and lunch breaks.

The client engaged Hatch to review their approach, assess different automation options, and make recommendations.

Solutions

Hatch configured a detailed scheduling model using the Hatch Optimizer to streamline the decision-making process. Hatch evaluated automation options for underground mine operations and quantified the impact on the overall production and crew utilization. As a result, the client was able to:

• Understand maximum throughput for the mine’s current state of automation and for different automation options.
• Identify the best operation strategy under future automation options.
• Avoid costly assumptions by detailed optimization of operations under each scenario.
• Understand the impact of automation on operation sequencing and workforce utilization for different automation options, as well as uncover new bottlenecks in the system.

Highlights

• Efficient determination of optimal operation for each automation option—get the best solution the first time around.
• Maximize the overall production throughput under a new operation environment.
• Identify the best operation pattern and crew allocation for each automation option.
• Identification of system bottlenecks and the best way to work around them through a holistic, simultaneous optimization of production and conveyance.
• Simultaneously incorporate production potential, equipment capacities, and crew constraints such as manpower required to perform tasks, shift changes, and lunch breaks.