SHORT-TERM MINE PLANNING

In open-pit mining, short-term planning focuses on creating a dependable production schedule that aligns with the long-term vision. The resulting short-term strategy needs to adhere to mining, processing, and plant limitations while optimizing key objectives such as overall metal yield, net profit, blending, or striping ratio. At APMT, we continually innovate, developing tailored algorithms to offer client-specific solutions on:

LONG-TERM PRODUCTION SCHEDULING

In open-pit mining, long-term scheduling determines the extraction timeline for blocks and sets the appropriate cut-off grades, and bench/phase definition. This schedule is optimized to maximize the project's net present value while aligning with corporate strategies, considering mining, processing, and metallurgical constraints, and maintaining balanced stripping ratios. At APMT, we employ advanced algorithms to address and analyze long-term mine planning challenges, including:

MINE SCHEDULING WITH REINFORCEMENT LEARNING

At the frontier between AI research and mining application, we reframe the problem of mine scheduling as a reinforcement learning task for short-term and long-term planning. Using a strategic workflow we provide optimal mine plans accounting for:

GRADE CONTROL MODEL

Grade Control aims for the integration of data from different sources and supports into the resource models to deliver more accurate local grade and geological attribute estimates. At APMT we focus on delivering: