Research Project
SERENA: working with ease by predicting failures
A research project to simplify maintenance activities by reducing time and costs and by improving the processes productivity.
Where: international
Where: international
Challenge
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.
Approach
SERENA project aims to enable predictive maintenance in different industrial sectors through a secure and highly modular cloud solution that can be tailored according to end-users needs.
Digital Ecosystem
Solution
Digital Ecosystem
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
Financing Framework
Results
Increased productivity of the processes
Simplified tasks for maintenance workers and plant managers
Technologies
Cloud
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Security
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AI & Data
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AR MR VR (XR)
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