On-Premises AI Enables Secure Drive Monitoring

Siemens has launched Drivetrain Analyzer Onsite, an on-premises analytics solution that uses Industrial AI to monitor and analyse drivetrain performance locally, addressing the need for secure and real-time data processing in industrial environments.

Context: Balancing analytics with data sovereignty
Industrial operators increasingly rely on data analytics to optimise performance and prevent failures. However, many applications—particularly in regulated or isolated environments—require strict control over data, limiting the use of cloud-based solutions.

On-premises analytics systems provide an alternative by enabling advanced data processing while keeping all information within the user’s infrastructure.

Technology: AI-driven local analytics
Drivetrain Analyzer Onsite processes high-resolution sensor data directly on industrial PCs, using AI-based pattern recognition and anomaly detection to identify deviations in drivetrain behaviour.

The system captures vibration data, analog signals, and operational parameters, which are preprocessed and analysed locally. This enables early detection of wear, mechanical changes, and potential failures without relying on external data transfer.

System architecture: Modular and integration-ready
The solution uses a containerised software architecture and supports standard industrial communication protocols such as MQTT, gRPC, and OPC UA. This allows integration with SCADA systems, edge platforms, and maintenance software.

Data is consolidated and visualised through a browser-based interface, providing plant-level overviews, KPI trends, and detailed diagnostic dashboards.

Portfolio positioning: Complementing cloud analytics
Drivetrain Analyzer Onsite complements Siemens’ cloud-based drivetrain analytics offering. While the cloud solution enables cross-site analysis and fleet management, the onsite version is designed for environments with strict data sovereignty, low latency requirements, or limited connectivity.

Both solutions follow a modular approach, allowing users to select deployment models based on operational and regulatory needs.

Applications: Industrial machinery and infrastructure
The system is suited for a wide range of applications, including production machinery such as extruders, packaging systems, and textile machines, where early detection of process deviations is critical.

It is also applicable to infrastructure systems such as pumps, compressors, and conveyors, as well as motion-control systems with dynamic operating conditions.

Operational impact: Predictive maintenance and reliability
By enabling continuous condition monitoring and early fault detection, the solution supports predictive maintenance strategies, reducing unplanned downtime and extending equipment lifespan.

Local processing ensures rapid response times and eliminates dependency on external connectivity, enhancing operational reliability.

Conclusion: Secure analytics for industrial environments
Drivetrain Analyzer Onsite addresses the growing need for advanced analytics in environments where data security and control are critical. By combining AI-driven insights with on-premises deployment, Siemens enables more reliable and efficient operation of industrial drive systems.

Edited by an industrial journalist, Lekshman Ramdas, with AI assistance.

www.siemens.com