Schedule Optimization

1. Consider your real production

In the early years of the project you will find a lot of concerns and the most value in terms of NPV. Knowing that, we decide to consider a 10-year surface to optimize the first 5 years. By an obvious assumption, as the surface used corresponds to a decade, it will contain the interval from the 1st to 5th period and represents a lot more mass. However, this simple input can restrict the space where the algorithm has to find a solution which could reduce the run time and help it to deliver better results respecting the set of constraints given.

Example:

    • Processing capacity: 10 Mt per year.

    • Total movement: 40 Mt per year.

    • Maximum of 4,000 processing hours in 5 years.

    • Vertical rate of advance as 150m per year.

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

    • Restrict Mining Surface: Surface002 from Exploratory Analysis.

    • Grade copper until 0.7%.

    • Stockpiling parameters on.

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1.1 Comparing Results

Notice that by running the scenario Exploratory Analysis, which corresponds to a 5-year package, we could just reach 44.6 Mt of production although there was a capacity of 50Mt. The aspect which caught our attention is that the processing hours constraint was in its limits, which probably is the main variable interfering in the processing capacity.

By running scenario Schedule Optimization, in a yearly bases guided by that corresponds to a 10-year period, the firsts 5 years achieved 48.8 Mt respecting the set of constraints. Therefore, by using this efficient workflow to focus on the most important periods we could reduce the runtime to take decisions and enhance our whole reporting with this data.

Considering this example we start to understand how can we optimize better the initial periods of our projects. You can also limitate your schedule with surfaces from step Best Case if more efficiency is needed. This multi-period optimization could take longer, so it’s also recommended to be run in a powerful machine, in parallel, while other tests are performed. Another useful tip is to add constraints gradually this run so that we can identify conflicts among them and/or bottlenecks. At the next step, we start to refine our results, since we already have a broader view we can decide which way you should attempts can we try to solve the challenges of the project.

Remember all the constraints


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