22 September 2022

VIR2EM: implementing virtualization in manufacturing

Virtualization, remotization and cutting-edge innovations: here are the results of the VIR2EM project!

VIR2EM is a highly innovative project run by Veneto's IMPROVENET Regional Innovation Network (RIR), of which Galdi is a partner.

Local companies collaborated closely with the Universities of Padua, Verona and Venice on the project, which started in September 2020 and ended in September 2022 with the official presentation of the results.

Shared goal: implementing "virtualization and remotization for effective and resilient manufacturing".

Added value: development of a common knowledge base across participating organisations through the sharing of know-how and novel insights.


Within the VIR2EM project, Galdi's team has focused on four R&D areas:

Digital Twin

Coordinated by Galdi's R&D Manager Michele Vazzoler and carried out in cooperation with the University of Verona, the project is leading to the development of a "digital twin" that simulates the functioning of one or more packaging machine components (e.g.: dosing unit).

The introduction of such a virtual system will open up new possibilities.

With ideas and innovations being tested with a simulator, we no longer need to run tests on a physical test bench and on the real machine.

Virtualization will be a big step forward in terms of product development. It will simplify the analysis, design, verification and validation of our filling machines and processes, and also allow for better communication between Galdi design engineers and technicians, making the whole process more efficient.

The immediate result for us and for our customers will be the ability to reduce time to market. Furthermore, our packaging machines will be even more reliable and “robust”, thanks to repeated testing through simulations.

Digital Twin applications, along with Big Data analytics, will also help us to understand even better how machines work over time, enabling us to take a further step towards predictive maintenance.

This also paves the way for the design of increasingly adaptive machines that can adjust settings autonomously in order to guarantee optimum efficiency at all times.

Predictive Maintenance

The international scientific community has recognized the innovative work Diego Tosato, Galdi's Software Engineer and Data Scientist, has carried out in cooperation with Statwolf and the University of Padua.

The dataset created during the project has been publicly shared, providing a benchmark for Alarm Forecasting.

In very simple terms, the system uses Artificial Intelligence to filter machine-generated data and detect unusual anomalies among the thousands of alarms that are reported on a daily basis.

It therefore improves the machine's ability to recognise and flag malfunctions, a key condition for predictive maintenance, but also to process data in a meaningful and relevant way.

Drawing on these insights, we are already developing a service to select and inform customers about significant anomalies, and more research related to Continual Learning is underway.

Two research papers were published: "FORMULA", on IEEE Transactions on Automation Science and Engineering, and "A Multi-label Continual Learning Framework to Scale Deep Learning Approaches for Packaging Equipment Monitoring".

Denis Deronjic and Enrico Convento, students at the University of Padua, also carried out research for their dissertations as part of this project.

IIoT infrastructure update

A general machine software update and the upgrade of the whole IIoT infrastructure gave us the opportunity to further enhance the capabilities of our systems in terms of quality and cybersecurity.

After conducting an analysis of existing issues and evaluating new solutions, the following actions were implemented to optimise our IIoT infrastructure:

  • Software and security update of the Edge Node data collection device
  • Installation of a diagnostics software that simplifies the work of technicians
  • Automatic configuration of the Edge Node data collection device
  • Security update and dataflow encryption on the Public Cloud (AWS - Amazon Web Service)
  • Installation of a new Edge Gateway/Firewall device for better connectivity and security control
  • Installation of a mobile interface on the Edge Gateway/Firewall device to improve connectivity and facilitate remote support activities by Galdi technicians

Following the update, the system can also be connected to a larger number of machines. This will allow us to get more relevant data on the functioning of our machines, which is crucial for Machine Learning, and also to support our customers more effectively.

Massimo Gallina, Galdi's IoT Manager, has overseen the project.

Virtual workstations

To make the work of our design engineers more agile and efficient, we created virtual workstations, installed on dedicated servers.

All members of our design team, as well as external collaborators, can get secure access from any PC, knowing they can rely on high-performance servers and state-of-the-art technologies.

Andrea Mattiuzzo, Galdi's ICT Manager, was in charge of the project.

We are proud to have participated in the VIR2EM project and obviously delighted with the results we have achieved.

We are confident that our research work will help other companies with their virtualization and remotization efforts, in line with the very principles of the project!