Computer Vision in the mining industry
Computer Vision
The automated visual inspection cameras/drones and AI to detect faults, measure and quality control processes in real-time. Fewer arrests, more security, and decisions traceable in the control room.
Predictive maintenance of machines
On the basis of the sensors and data existing in the evaporation ponds, collect real-time data on levels of brine, temperature, humidity, and concentration of lithium, allowing you to visualize these data in a panel of centralized control
Conveyor belts
Through the creation of mathematical models, based on data, to simulate the reactions that occur in the evaporation ponds. Perform multiple simulations to test different scenarios, such as changes in climatic conditions, or in the levels of brine, without interrupting the real-world operations.
Agglomeration
Through the implementation of Algorithms of Machine Learning, analyze historical data and predict future trends, as the rate of evaporation and the concentration of lithium.
Leaching
To continually adjust the process parameters to maximize the recovery of lithium. On the basis of historical data, to generate recommendations for operation of the variables actionable greatest impact they have on the better result of the process
Integration and deployment
We start with minimal integration, we define KPIs and operate in parallel before you can enable automatic actions.
- Existing cameras
- Drones/thermography
- PLC/SCADA/DCS
- CMMS/Maintenance
- Data lake/boards by role.
Other cases of application
Quality Control for monitoring the concentration and uniformity of the solution lixiviante, early detection of obstructions in the distribution networks of acid to prevent operational problems, and monitoring of the reaction of leaching to adjust parameters of the process in real time.
