# 1. Introduction

For a mining project, the mine planner needs to dimension each unit operation to assign which set of equipment will best suit the existing conditions. On MiningMath, the operational parameters are constraints to the objective function, instead of being applied after pit optimization. This approach allows for solutions that follow either some operational criteria and maximizes NPV, resulting in a better use of the data and identifying opportunities that could be missed by an approach with manual steps and arbitrary assumptions.

## 1.1 Geometries & the User Interface

The Geometric tab is the place to set minimum mining & bottom widths, and vertical rate of advance, whose values are applicable to every period. The user can also use surfaces to define operational constraints in compliance with period ranges, which can limit, force or achieve an exact shape, based o the constraints hierarchy.

### Minimum Widths

Figure 1 shows the fields where define widths:

• Mining Width: Distance from a pit to another.

• Bottom Width: Bottom minimum area.

Currently, MiningMath does not mine partial blocks. As a consequence, the software will round up any widths to cover the next integer block .

### Vertical rate of advance (VR)

Figure 2 where input VR, also known as sinking rate:

• Maximum

As said before, the MiningMath will round up the VR to cover the next integer block.

Figures 3-5 show a simplistic meaning of each width available and the vertical rate of advance.

Figure 3: Minimum bottom width.

Figure 4: Minimum mining width.

Figure 5: Vertical rate of advance.

### Surface Mining Constraints

For each period range, the user can consider:

• 1 force mining surface

• 1 restrict mining surface

Each surface file is valid from period A up to final of period B, as highlighted in Figure 6.

Figure 6: Surface mining limits: forcing and restrict mininig.

## 1.2 Practical Overview: How to play with operational parameters

The following video shows how the variation of operational constraints impacts your solution and how you can take advantage of these parameters to find results more closer to the reality.