Javier Nieves, PhD.
“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.”
Intelligent Manufacturing Technologies
REVaMP. Retrofitting equipment for efficient use of variable feedstock in metal making processes
Proyecto en curso 0% 0 Start date Horizon 2020 Funded
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
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
Explaining Industry 4.0 to my Grandma
Nowadays it is really easy that some kind of Anglicism
Procedure for predicting the mechanical properties of pieces obtained by casting
Procedure that enables future mechanical properties to be determined based
Worldwide foundry industry exhibits its latest advances at GIFA
Once again, Düsseldorf has been the center of world foundry
Industry 4.0 Factory of the Future (FoF). Reality beats fiction.
Latest technology advances have been able to blend digital and
Enhancing the stationary state prediction in Model Predictive Control systems to avoid Dross defect in heavy-section foundries
A Model Predictive Control (MPC) is a system designed to
Supervised learning classification for dross prediction in ductile iron casting production
Foundry is one of the key axes in society because
Iron castings Advanced prediction tools, foundry process control and knowledge management
It is well known that the large number of variables