Blockchain developments are provided for a vehicle manufacturing project in Spain

Eurohelp Consulting (a company integrated into the Amatech Group) participates in the Fandango project, which focuses on the advanced manufacturing of automotive components. The project, led by Estampaciones Mayo, is based on the development of “zero defect” vehicles. of technologies such as the digital twin, blockchain and deep learning. This was reported to Cointelegraph in Spanish through a statement from Spain.

to????Eurohelp’s participation focuses on the application of blockchain technology to ensure the access and integrity of the information through the entire manufacturing process and give this Industry 4.0 project a plus in security and reliability – so it says in the statement.

â ???? Blockchain enables us to establish a secure channel for the exchange of information between the partiesâ ???? commented Arkaitz Carbajo, technical director for research and development at Amatech Group.

Operational EfficiencyÂ

Blockchain developments are provided for a vehicle manufacturing project in Spain
Blockchain developments are provided for a vehicle manufacturing project in Spain

As detailed, the project is dedicated to improving operational efficiency in the automotive components sector with three primary goals: visibility of information throughout the supply chain, maximizing product quality, and optimizing processes that have no direct value (predictive maintenance).

â ???? In this way, on the technological basis of the digital twins developed by Tecnalia together with the companies Fagor and Segula, which recognize problems and predict the results of processes with greater precision than the models of pure. enable simulation, complementary technologies are used. On the part of Eurohelp, blockchain to ensure shared information; on the other hand, artificial vision systems from Tecnalia and Grupo lava, with the aim of improving and further improving the quality standards in production lines through the implementation of deep learning algorithms for the detection of multiple defects, they specified

You might be interested in:

Similar Posts