“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.”
Obtaining Perfect Critical Automotive Safety Components through Behavioral Monitoring and Simulation using Digital Twins
With the aim of obtaining the perfect component and manufacturing
An Objective Metallographic Analysis Approach Based on Advanced Image Processing Techniques
Metallographic analyses of nodular iron casting methods are based
New Approach to Develop Ductile Cast Iron Digital Grade for Automotive Components
This research work demonstrates that new cast iron materials can
Industry 4.0 for aluminum foundry: an optimal management of the process to enhance competitiveness of the company
A standard HPDC industrial manufacturing process is likely to present
A sound vacuum system fully monitored to ensure the quality of the HPDC components
Gas porosity is an intrinsic feature of the HPDC process
Additive Manufactured inserts for Industry 4.0 HPDC Foundries
Researcher Emili Barbarias explains two case studies regarding advanced monitoring
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
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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