# 1. Work Through Different Timeframes

Identify timeframe intervals in your project, so that you can work with group periods before getting into a detailed insight. This strategy allows you to run the scenarios faster without losing flexibility or adding dilution for the optimization, which happens when we reblock.

The idea is to make each optimized period represent biennial, triennial, or decennial plans. MiningMath allows you to do it easily by simply adjusting some constraints to fit with the timeframe selected, as shown in the example below. Try to run with and without dump/total productions to check potential bottlenecks and impacts on waste profiles, which could be useful for fleet management exercises. Also, test with wider mining widths than required, as this is a complex non-linear constraint and you might find better shapes without losing value. Notice that in this example, the processing was not fully achieved, and this kind of approach helps us to understand which constraints are interfering the most in the results.

MiningMath algorithm simultaneously considers all constraints inputted, making a global optimization to generate your pushback in a single step giving the maximum potential.

Example:

• Timeframe: Custom factor= 5.

• Processing capacity: 50 Mt in 5 years.

• Total movement: 200 Mt in 5 years.

• Maximum of 25,000 processing hours in 5 years.

• Vertical rate of advance as 750 m in 5 years.

• Minimum Mining (50 m) and Bottom(100 m) width.

• Restrict Mining Surface, if you have this constraint in your project.

• Stockpiling parameters on.

Note: Waste control and vertical rate of advance are not recommended if you are just looking for pushback shapes.

## 1.1. More details

Adding constraints slowly facilitates the process of learning about the deposit, its opportunities, and potential challenges. In case some constraints are not being well-achieved, it is an alert for rethinking some of them, as well as for the risk of not achieving them in the shorter-term ranges.

In case more efficiency is needed, the resulting surface obtained on the Constraints Validation or in Best Case refinements could be used as Restrict Mining in the last interval, which might reduce the complexity and the runtime. In addition, if you already have operations in a certain area that should be depleted following a given design within the first timeframe, add a Force Mining surface for interval 1-1.

The 4 first variables of this example are directly related to the interval in which we are working. The 2 constraints inputted at the production tab are related to the maximum material handling allowed: the third one is about the processing equipment capacity, and the vertical rate of advance is related to the depth that could be achieved adjusted to this interval. The minimum mining width was added because we are already generating designed surfaces that could be used later as guidance of detailed schedules, thus, it should respect the parameter due to the equipment sizing. Parameters such as average, minimum bottom and restrict mining surface, don't suffer any change in the time frames.

It's important to remember that the packages of time here donβt necessarily have to correspond to identical sets of years. You could propose intervals with different constraints until reaching reasonable/achievable shapes for the design of ramps, for example. If you wish to produce more operational results, easier to design, and closer to real-life operations, try to play with wider mining/bottom widths rates. Those changes will not necessarily reduce the NPV of your project.

Considering this approach the discount rate serves just a rough NPV approximation and it doesn't affect much the quality of the solution, given that the best materials following the required constraints will be allocated to the first packages anyway.

Remember all the constraints