Beginning of maintenance 4.0 project at SIAAP

Ecology factory small wastewater.

SIAAP, the public reference for wastewater treatment in the Ile-de-France region, embarked in 2016 on the design of a long-term strategic plan: SIAAP 2030. It aims to implement a medium-term conditional and predictive maintenance strategy. Among the challenges pursued: improving the maintenance of its industrial equipment, in particular the real-time monitoring and diagnosis of critical equipment, with advanced analysis techniques (IoT sensors, AI). And it’s our innovative BL.Predict platform that has been selected to meet the challenge!

An experiment conducted on critical equipment

This experimentation of connected and intelligent maintenance will start in December. It will be conducted on critical equipment: bar screens. Screening is a water treatment operation designed to trap materials and all kinds waste contained in the inlet channel of a hydraulic structure or at the pre-treatment stage of domestic, agricultural or industrial wastewater, so that they can be extracted, then stored in a skip and evacuated to a treatment route.

Screenshot Predict.
Fig. 1 – Overview of a BL.Predict interface

Involvement in the entire value chain

BL.Predict integrates the entire Internet of Things chain: connected objects, data storage, data exploitation, data visualization and interoperability with our maintenance management solutions (i.e. CARL Source). In a first phase, BL.Predict will monitor and analyze the hydraulic motor pump, its electric motor and the hydraulic system (cylinders for moving the grids). To do this, BL.Predict will collect measurements of the hydraulic system’s vibrations, the motors’ electrical consumption, operating temperatures and the level of particles in oil.

Finally, BL.Predict will embed AI for diagnosis and failure prevention (prognosis).

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