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Optics Virtual 2020

An innovative RAMI 4 compliant network design for predictive maintenance on automatic testing equipment

Davide Cascella, Speaker at Davide Cascella: Speaker for Optics Conference
GEM ICT srl, Italy
Title : An innovative RAMI 4 compliant network design for predictive maintenance on automatic testing equipment


The continuity of service of the machines during the test cycles is essential for customers. That is why ELES Semiconductor Equipment SpA, manufacturer of machines for testing electronic components, decided to invest in IIoT solutions. In particular, the main objective of this research project was to design and create an optimal network architecture according to RAMI 4.0 (Reference Architectural Model for Industrie 4.0), in order to perform disaster recovery and remote control of the equipment by exploiting the computational, storage and network load sharing offered by the cloud. This is configured as an innovative solution, placed between edge and cloud computing, crucial for the good implementation of services. This solution helps customers to do predictive maintenance on components and reporting, with a significant reduction in hardware costs, while it helps the manufacturer to access data from sensors and offer support, with a lower expenditure of human and economic resources and from anywhere. The main benefits of a RAMI 4.0 solution are: • Service-based architecture: each company can implement its activities as it sees fit. • Combine the physical elements with the life cycle of the whole process in order to find the right points of contact between theory and practice. • Complex processes are divided into smaller and simpler developments so that they can be better managed. • The devices communicate and collaborate with each other through a network without hierarchy constraints. • The devices on board can be cyber-physical systems, terminals and applications through which operators interact with the system. The activity included configuring field to cloud connectivity, collecting, organizing, processing and storing data, monitoring operational metrics in near-real time and alerting. The implemented solution is scalable, cost effective and secure, and offers flexible access with operational dashboard and alerts. It makes available self-serve analytics and BI reporting.


Davide Cascella was born on April 1980. He received the MSc degree and the PhD degree in Electrical Engineering from the Polytechnic University of Bari. He is author of 20+ peer reviewed scientific papers on industry 4.0 and AI applications. He currently works as Innovation Manager and Industrial & Process Automation specialist. He is also responsible for technological innovation and energy efficiency projects, enabling the digital transformation and the adoption of Industry 4.0 Key Enabling Technologies in manufacturing companies.