Predictive Analytics and Machine Learning
Deliver better business outcomes with accurate and actionable insights
The Seebo IIoT Platform uniquely combines the IIoT Model with the OT and IT data, and then applies machine learning and advanced analytics to derive actionable insights. These insights are used by operational teams on the ground – through the Seebo Predictive Maintenance, Seebo Predictive Quality and Seebo Predictive Wastesolutions – to maximize overall equipment effectiveness (OEE), reduce unplanned downtime, and uncover the root cause of manufacturing issues.
Process-based digital twins provide intuitive visualization to understand the real-time condition of production lines. Predictive alerts, powered by machine learning and AI, deliver deep insight into upcoming downtime and quality disruptions, including automated root cause analysis.
Automated Root Cause Analysis – faster, more reliable results
By implementing Automated Root Cause Analysis, there is accurate visibility into early causes of process inefficiencies, with a low amount of alerts and false positives. Automated Root Cause Analysis generates actionable insights, enabling you to reduce unplanned downtime, increase production throughput, and minimize quality issues.
By fusing historical and real-time machine data into process flows and production batch data, machine learning algorithms trace correlations between the consolidated data and the process inefficiencies.
Seebo ranks the root causes by likelihood level, delivering production teams with prioritized suggestions to quickly mitigate process inefficiencies that impact production yield and quality.
Predictive Simulation
Once machine learning predicts upcoming process disruptions,there’s a need to determine how the anticipated production disruption can be avoided by changing specific production parameters.
With thousands of production parameters at hand, it’s unclear where to start. This is where Automated root-cause analysis should be used to determine the specific causes of an upcoming disruption. After understanding the disruption causes, predictive simulation is used to enable the user to determine the best-fit values in order to avoid the process disturbance.
Industrial IoT Solution Modeling
Create a digital model for your industry 4.0 solution
Your envisioned industry 4.0 solution includes physical equipment, sensors, communication protocols, data analytics, and dashboards. Use Seebo to visualize your solution blueprint.
Accelerate solution modeling by using prebuilt solution templates – for predictive maintenance, predictive quality, condition monitoring, and more – and customize the solution model to meet your exact needs. The Seebo IoT Modeler includes a library with hundreds of sensors, PLCs, gateways, data analytics algorithms, and dashboards. Drag and drop the IoT components, and visually define the logic for your solution.
Industrial IoT Data Integration
Streamline IIoT development with connectivity to your OT and IT data sources
The Seebo Industrial IoT Platform cuts implementation time and costs with built-in OT and IT data integration gateways and connectors.
Data from your production line – generated by your physical assets – is securely captured using OPC UA or your company’s preferred IIoT communication protocol.
The Seebo platform also includes connectors to leading commercial ERP and Quality Management systems to enrich your time-series operational data with context that is critical for effective data analytics.
Technology stack based on Microsoft Azure
Seebo is a Microsoft technology partner. Our process-based AI solutions are based on the Microsoft Azure cloud platform for scalability, security, and proven resilience.
- Seebo IIoT solutions come with built-in scalability, security, and performance to meet the demands of mid and large-size enterprises
- Quick integration with other Microsoft and third-party, cloud-based services
- Microsoft Azure services are bundled as part of the Seebo solution, making licensing the Seebo platform simple and cost-effective
