In this webinar, we will address how maintenance strategies affect the total efficiency of the factory, how to improve these strategies, and how to reduce costs due to downtime.
We will present a strategy that uses statistical modeling based on Machine Learning to study anomalies, combined with real-time sensor data to predict them.
A real case showing how TIBCO Software helped a manufacturer save 10% on maintenance costs will be used to illustrate the strategy
Presented by:
Alessandro Chimera
Industry Consultant at TIBCO Software
Massimiliano Cassinelli
Scientific Director of BitMAT
Produced in collaboration with BitMAT Editions
Webinar BitMAT-Machine Learning e Industry 4.0 - La nuova predictive maintenance (1).mp4
Success with TIBCO:
2,000+
Spotfire users
Over $1 million
In projected opportunities
4 TO 6 HOURS
Time spent gathering data before Spotfire, now eliminated
1
centralized source of information, down from 10