Predictive Analytics for Manufacturing:

Take Advanced Action

Seebo Model-Based IoT Analytics utilize machine learning to
power predictive maintenance and predictive quality solutions

Get Demo

Predictive Analytics for Manufacturing: Take Advanced Action

Seebo Model-Based IoT Analytics utilize machine learning to power predictive maintenance and predictive quality solutions

Get Demo

Translate data into predictive insights – without data scientists

Applying industrial predictive analytics is usually complex and necessitates data specialists. Seebo Digital Twin Model fuses your performance metrics, process data flows, and your OT and IT data into machine learning – without requiring you to master data science.

Users design a digital ‘twin’ model of their production line that drills down into the production line architecture. The digital twin then overlaps data from multiple processes in the context of the physical production line, creating a rich point of reference that makes it easy to access and track insights and the data behind them.

The result – a virtual map of your production line that contextualizes predictive alerts, events, and historical data, for unmatched accuracy of insights.

Anticipate and prevent failure before it happens

Unsupervised Machine learning tools such as clustering and artificial neural networks are applied to historical data on machine failure, repairs, operating conditions and maintenance requirements.

These systems run algorithms to spot related events and predict numerous outcomes, resulting in automated recommendations on everything from fault lines in the production process to breakdowns of individual machine parts.

Predicting when an asset will fail, and the reason for that failure, enables operators to increase uptime and prevent costly quality defects.

Predictive Analytics accessible to manufacturing teams on the ground

Seebo Industrial Predictive Analytics provides simple and accurate forecasting for operational teams.

Users across the factory access customized dashboards, displaying role-specific alerts and overviews about predicted quality and production events.

By engaging with relevant predictive analytics in a user-friendly format, everyone from decision-makers to the teams on the factory floor can make more informed decisions and improve efficiency across the production process.