In industrial manufacturing contexts, downtime is a relevant reason for reduced productivity and profitability. Among the most common causes there are unexpected machinery failures. In recent years, great interest has been directed towards predictive maintenance solutions which, by providing insights on equipment deterioration, allow to anticipate failures and hence to reduce time and costs related to maintenance activities.

The SERENA project has optimised the equipment maintenance process at plant floor, reducing time and costs, by delivering distributed advanced data analytics services in a modular, plug-n-play and secure hybrid edge-cloud environment equipped with a robust data storage, an efficient broker and tools for supporting plant operators (dashboard, scheduler, AR-based assistance). We as Engineering are responsible for the architecture design and have provided integration pipelines for all the component modules, developed a dedicated security middleware and implemented a data ingestion and digestion layer. Finally, we have validated the solution in several use cases: Whirlpool, COMAU, Trimek, VDL and Kone. The project has received funding from the European Union's Horizon 2020 programme - Contract No. 767561