PUMP

PUMP solution applies existing non-intrusive energy monitoring tools and advanced ML models to analyse the patterns in electrical loads of machinery equipment, disaggregate component loads, and detect deviations from normal operation in a processing plant. PUMP offers real-time energy monitoring, Energy Efficiency tips, process optimization and maintenance planning, equipment health monitoring and identification of possible signal anomalies through an IoT platform.

Leveraging several KYKLOS 4.0 components such as the LCA and DSS, the end-users are allowed to plan more efficiently their maintenance actions and ensure proper and timely service of the equipment, while raising awareness of the environmental impact of their processes.

The solution utilizes KYKLOS 4.0 components along with already developed tools to utilize data collected from the factory shop-floor regarding the production process and energy consumption of various equipment, in order to measure and increase the circular approach of the industry. More specifically, the insights offered by the LCA component will help towards increasing the upcycling percentage of the materials over the total mass of product, while the optimization of maintenance planning along with the identification of possible equipment faults may increase the Use Phase Circularity indication, extending the lifespan of utilized equipment.

The PUMP Experiment has indirectly received funding from the European Union’s Horizon 2020 research and innovation action programme, via the KYKLOS 4.0 Open Call #2 issued and executed under the KYKLOS 4.0 project (Grant Agreement No 872570)