“Artificial Intelligence and advanced control systems allow us to deepen our knowledge of the process, standardize it and develop tools that help industrial companies be more efficient and produce without defects.”
A Smart Digital Twin to Stabilize Return Sand Temperature without Using Coolers
In order to ensure the optimal state of recovered molding
New ductile cast iron digital grades for automotive components
This research paper demonstrate that new cast iron grade materials
Towards the Prediction of Tensile Properties in Automotive Cast Parts Manufactured by LPDC with the A356.2 Alloy
Aluminum-silicon-magnesium alloys are commonly used in the automotive industry to
Manufacture of forming tools with subcutaneous cooling circuits by means of laser cladding
In the manufacturing processes of transformation of metallic, plastic, and
New generation of digital material for automotive components
With the application of Industry 4.0 technology, a new generation
Visit AZTERLAN’s booth at Euroguss 2024
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Metallurgical process control to optimize iron castings
20/01/2021 After thousands of years among us, foundry still encloses
REVaMP. Retrofitting equipment for efficient use of variable feedstock in metal making processes
Project complete 0% 0 Start date Horizon 2020 Funded by
Digital Twins workshop
AZTERLAN’s Industry 4.0 expert and head of Intelligent Manufacturing Technologies
Shaping the foundry of the future by means of the “perfect casting”
03/09/2019 In the month of June took place in Dusseldorf
Chunky graphite in spheroidal graphite iron: Review of recent results and definition of an predicting index
Graphite degeneracy in heavy-section spheroidal graphite cast irons is mostly
DigiMAT. Digital Materials for the Automotive Industry
Project completed 0% 0 Start date H2020 Funding 830903 Grant
Cyber-security, the forgotten item in Industry 4.0
The “Industry 4.0” or the “Factory of the Future” has
Statistical Study to Evaluate the Effect of Processing Variables on Shrinkage Incidence During Solidification of Nodular Cast Irons
The study of shrinkage incidence variations in nodular cast irons