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Date: April 17, 2018
Predictive Thickener Model
Automation and robotization

Project Leader:

Pablo Cheng, Superintendent of Development.

Challenge:

Water is a key resource for mining development, and taking into account that most of the operating mining plants are based at the dessert, away from access to water, a rational use and reclaiming of the same, play a critical role.

Solution:

Implementing a predictive model to optimize the operational performance of thickeners, thus allowing to thicken tailings to a high density level, with a percent of solids of over 65%, and incrementing water reclaiming.

Objectives:

1. Identifying the process variability root cause.

2. Predicting and making recommendations to adjust the operational variables.

3. Diminishing the operational range.

4. Optimizing mass balance to ensure the equipment stability.

5. Consistently reaching the final solids target.

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