Boosting Mine Profitability with Optimal Pit Boundaries in K-MINE

Why Economics Drive Open-Pit Decisions

Every mine planning engineer eventually faces the same challenge: meeting strict economic targets. Lowering costs and increasing profitability boosts project attractiveness, opens new opportunities, and helps unlock the full value of a deposit. This video shows how the Optimal Pit Boundaries module in K-MINE can materially improve project economics.

Project Setup for Pit Optimization

We begin with an optimization project where key parameters are defined: final slope angles, price adjustment factors (PAF), excavation and haulage costs, processing costs, recoveries, and the cutoff grade. To enhance accuracy, processing costs and metallurgical recoveries are calculated by formulas tied to ore quality – slightly increasing run time, but significantly improving the fidelity of results.

Selecting the Economic Pit Shell

Using built-in charts, diagrams, and tables, we review pit shells and select the scenario aligned with our criteria. In this example, the pit contour at a PAF of 0.7 is chosen as the most balanced option.

Running Sensitivity Analysis

Within the optimized project, we run a sensitivity analysis across a defined range of adjustment factors and evaluate key outputs. Two views guide decisions: a general economics tab (revenue, profit, NPV) and a product-specific tab (grade and recovery-dependent metrics). The analysis clearly shows where parameter reductions improve profitability.

Insight: Cutoff Grade as a High-Impact Lever

On the product-specific tab, one finding stands out – lowering the minimum cutoff grade significantly increases project profitability. Because processing costs are quality-dependent (via formulas), incorporating more lower-grade ore does not require additional capex or special measures, making this a practical lever.

Scenario Test: Lowering Cutoff Grade from 15% to 12%

We copy the project and reduce the lower cutoff grade by 20% – from 15% to 12% – then recalculated. Visually, more ore now reports to processing. The key question is economic: does this translate into better financial outcomes given quality-linked costs?

Results: Revenue, Profit, and NPV Rise

Under the same PAF (0.7), the improved scenario delivers:

• Revenue ≈ 5.5B

• Profit ≈ 3.7B

• NPV ≈ ~2.0B

Compared with the baseline:

• Revenue ≈ 4.0B

• Profit ≈ 2.7B

• NPV ≈ ~1.7B

Net effect: +1.5B in revenue, +1.0B in profit, and roughly +300M in NPV.

Takeaway for Mine Planners

Meaningful gains don’t always require major investments. With K-MINE’s Optimal Pit Boundaries, data-driven adjustments – like optimizing the cutoff grade using grade-based cost and recovery formulas – can materially lift project value. Keep testing scenarios, measuring outcomes, and iterating to capture more value from every bench.