Digital Factory Pilot Line

Distributed intelligence systems are based on the use of cooperative systems, organized in hardware or software components, that independently handle specialized tasks to achieve system-level goals and achieve a high degree of flexibility. Industrial edges allows data produced by sensor-rich assets like machines, equipment and devices to be pre-processed in real-time, closer to where created, merging industrial IoT data with operational data. Companies can also leverage on cloud system where to extensive process those aggregated data, where is today possible execute mission critical services and develop artificial intelligence driven business intelligences logics.

Extended reality (XR) represents the miscellaneous of augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies, which tackle various manufacturing domains such as training, education, safety and simulation. Thanks to commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies, shortening the gap between 3D modeling and virtual environment creation. Technologies like holographic viewer, virtual glasses, smart glasses, smart helmet becomes commodities to design virtual simulation and training, as well as augmented operator features, that also changes the manufacturing business paradigm.

The industry 4.0 technologies adoption brings new cyber risks, from operational to business. With the interconnectedness of the smart factory technologies, cyber threats are among the most prevalent, as smart factory environments expose people, technology, physical processes, and intellectual property to these risks. The games is so changed: yesterday cybersecurity was preventing any external connection within the shopfloor, but today, if machine are connected to the cloud, cybersecurity means to guarantee a vertical, active and exhaustive IT/OT protection.

Manufacturing industries worldwide constantly try to improve their productive performance. Lean Production and World Class Manufacturing are the most popular strategies which companies adopt to boost production efficiency. But it is not just for big enterprise, it is applicable to multiple scenarios and to small medium enterprises too. Digital technologies also support the adoption of those best practices, in the process design phase as well as at operational level.

Predictive maintenance aims at using data analysis tools and techniques to detect operation anomalies and possible equipment defects in order fix them before the actual failure. Ideally, predictive maintenance allows the maintenance frequency to be lower possible, preventing unplanned maintenance and without facing costs associated preventive tasks. But it is not a turnkey solution: it means to define a complex plan that deals with data acquisition, data aggregation, cybersecurity, and data management policies issue. It includes designing logics and instruments, as well as the proper user interface to support maintenance stuff to better perform their job.

The architectural concept of future core and access networks, which will enable extensive and distributed capillary broadband network to connect companies and shopfloor. Incoming mobile wireless connectivity, like 5G and WiFi6, delivers a boost in connection speed, improvement in battery life, increase in network capacity, and bandwidth growth over previous generations network. When it comes to Industry 4.0 use cases, it will facilitate the adoption of ultra low-power IoT sensors, low latency for improved XR, real-time location services (RTLS).

Adopting Industry 4.0 is not always about huge investment or the creation manufacturing greenfield: most of the times is to identify and apply the proper digital COTS available technologies within situ equipment, for example to allow the gathering of data which can then be used to inform production decision-making in real time. It is about doing small steps, studying the brownfield and the specific company needs, avoiding redesigning equipment or purchasing expensive apparatus. And it is about evaluate value added, production efficiency is the driver to tackle the competitiveness.