Predictive maintenance : no more machines failures
Spare parts lifespan can be prolonged and the stocks quantity reduced through a failure prediction that cuts operating costs. It relies on the deviations modelling of key physical behaviours in the Studio.
The machine can detect these alone in real-time. The suitable action is then suggested to the workforce on the defective spare part. Operators on the shop floor are notified through the Share early enough to avoid production stoppages.
Create powerful predictive analytics
and increase the mean time to failure of machines
Complex deviation detection
Notifications directly to shop floor for action
Proactive maintenance operations accomplished
Sidel : Predicting filling valves’ deviation
SIDEL is a complete solutions provider that serves producers of water, carbonated soft drinks, liquid dairy products, juices, nectars, isotonics, soft drinks and teas. It is a leading provider of blowing, filling and labelling solutions for multiple applications, including food, home and personal care products.
We provide predictive maintenance services to our clients powered by Sidel InUse. We help them to solve problems before they happen. As such, we’re closely involved in our client’s performance, by contributing directly to the improvement of their production efficiency.
Key Figures
filling valves connected
increase of overall production efficiency
reduction of spare parts purchases
