Aetna Group's Robopac Group collaborated with Bi-Rex, one of the 8 national competence centers established by the Ministry of Economic Development, whose goal is to act as a strategic and operational support for companies oriented to the digitalization of industrial processes. Robopac reports the partnership allows it to implement its know-how and make it available to companies and SMEs, which represent 95% of the industrial network, fully reflecting the standards of the open innovation approach.
Robopac TechLab and Cineca, a computing center in Italy operating within the Ministry of Education, University and Research that offers support through supercomputing and its applications, are examples of private and public organizations within the Bi-Rex Competence Center.
"The Italian Competence Centres are able to bring together public and private, university and business research to possess all the skills and networking resources capable of developing innovative processes,” says Stefano Cattorini, BI-REX general director, in an interview with La Repubblica. “Public-private collaboration is absolutely crucial to accelerate growth.”
TechLab is a system of research laboratories in the packaging sector developed by the Robopac Group. The aim of TechLab laboratories is reportedly to allow the testing of technological solutions through a scientific approach, obtained with measurement and simulation equipment and through a testing method accredited by Accredia, which reportedly guarantees operability according to worldwide standards of competence, independence and impartiality.
In the private sector, a model of data usage aimed at the control of machines and optimization of the productive effect in maximum safety and with the minimum use of packaging materials comes from Bi-Rex's aim to provide companies with new business models and enabling services in the field of Industry 4.0 and Enterprise 4.0 — with technologies related to the collection and efficient processing of big data — from industrial cloud/edge to artificial intelligence applied to predictive diagnostics and machine learning.
This approach reportedly aims at offering skills and resources to a wide industrial sector, adopting the concepts of IoT (Internet of Things) and Digital Twin as models that can be implemented in different fields to achieve production performance, optimize resources and ensure environmental protection through energy and consumables savings.
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