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DIGITAL TWIN

Intelligent water dosing system for return sand conditioning

Ensure the optimal conditions for recovered sand, without the need for coolers

Ensure the quality of the recovered sand

Based on control software and a minimal network of sensors, this system can be installed in all types of green sand molding functions that wish to stabilize the outlet temperature of their return sand and its overall quality.

This smart system allows:

Digital twin of the return cycle of spend foundry
molding sand for a real-time control of production

A system tailored to each casting process

Capture and storage of key data

Data architecture and digital twin

Layout sensorización planta fundición arena de retorno
T1

Temperature of castings at the entrance of the drum

T2

Temperature of castings at the exit of the drum

T3

Temperature of parts prior to irrigation

T4

Temperature of sand prior to entering silos

H1

Humindity

Layout example of the implementation of commercial sensors in a demoulding line. Hover over the highlighted items to get details of the captured values.

A minimal network of sensors to capture key data

A virtual twin fed by equipment data and data captured by a minimal network of commercial sensors allow irrigation to be adjusted to the real-time load of the demoulding drum and conveyor belts:

Do you want more information about this solution?

We can help you develop a more efficient function process.

Team

Shaping the
Foundry of the Future

“The Foundry of the Future is that of connected processes that is able to take advantage of the knowledge generated inside the company at the same time that it keeps learning from its manufacturing and market experience.

Along with a deep knowledge of metallurgy, Industry 4.0 technologies, advanced data management systems and machine learning technologies have landed in this industry to transform the way castings are conceived”.

Susana Méndez, PhD

Susana Méndez, PhD
Director of Foundry Technologies

Aitor Loizaga

Aitor Loizaga
Iron Foundry Technologies

Asier Bakedano, PhD

Asier Bakedano, PhD
Light Materials

Dr. Javier Nieves

Javier Nieves, PhD
Intelligent Manufacturing Technologies

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