Learning MiningMath
Now that you have installed and tested MiningMath, we can move forward to understanding the fundamental concepts and the logic behind the software’s operation.
We will do this in two distinct stages: Essential MiningMath and In-Depth MiningMath.
Both paths follow a suggested sequence of key articles from our Knowledge Base. We recommend starting with the suggested reading order to get the best learning experience. Take this opportunity to familiarize yourself with the Knowledge Base, as we are confident that even after completing this initial learning journey, you will return to it many times for deeper insights.
In Essential MiningMath, you will be introduced to a collection of tutorials and fundamental articles designed to help you fully understand and make the most of MiningMath’s features.
By the end of this process, you should be able to:
Applying predefined scenarios and decision trees to optimize mine planning.
Understanding the logic behind MiningMath’s results compared to pre-existing technologies and gaining deeper insight into the software interfaces.
Preparing, validating, importing, and managing data and constraints.
Setting economic parameters for material allocation.
Optimizing and extracting results from MiningMath by exploring different parameters and workflows.
Exporting your results for integration with other tools.
Moving on to In-Depth MiningMath, you will gradually transition to the intermediate level, delving deeper into topics such as:
How to configure the Block Model, including handling improperly formatted data.
Defining, managing, and running scenarios.
How to analyze the results.
In addition to these topics, you will be introduced to a series of articles covering setup, workflows, fundamental theoretical aspects of the algorithm, and other more advanced content.
