How to predict equipment anomalies and act in real time
Maintenance affects the total efficiency of the factory. What maintenance strategies increase it and reduce the downtime costs?
Using machine learning, you can prepare a model of your factory, identify normal and abnormal states, then watch real-time sensor data to predict degradation and intervene to avoid inefficiency and downtime.
This webinar will cover:
- The newest strategies and how to anticipate problems using machine learning
- A real case where TIBCO Software helped a manufacturer save 10% on maintenance costs
New to Industry 4.0? Learn about it here.
Machine Learning & Industry 4.0 - Predict equipment anomalies and act in real time
Success with TIBCO:
3 vs. 10-12
Months to develop a real-time system with TIBCO Streaming vs. open source
$300K SAVINGS/MONTH
In electricity consumption via analytic-driven asset utilization