Siemens Drivetrain Analyzer Onsite New AI-Powered on-Premises Analytics for Industrial Drives

By Siemens | Translated by AI 2 min Reading Time

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Siemens’ new on-premises analytics solution bridges the gap between isolated machines and cloud-based platforms and is designed for users with high data sovereignty requirements. It processes drive data entirely within the user’s own infrastructure, including integrated industrial AI functions. Drivetrain Analyzer Onsite is part of Siemens Xcelerator

Drivetrain Analyzer Onsite (DTA Onsite) is a new on-premises analytics solution for industrial drivetrains.(Image: Siemens)
Drivetrain Analyzer Onsite (DTA Onsite) is a new on-premises analytics solution for industrial drivetrains.
(Image: Siemens)

Siemens introduces Drivetrain Analyzer Onsite (DTA Onsite), a new on-premises analytics solution for industrial drives. The software enables drive data to be analyzed entirely within the customer’s own infrastructure and meets strict data sovereignty requirements. The first feature of the new solution to be released is DTA Onsite—Monitoring. This feature provides continuous condition monitoring of mechanical and electrical components in the drivetrain, utilizing locally executed AI algorithms for pattern recognition and anomaly detection.

Monitoring As A New Feature for Local Condition Monitoring

DTA Onsite—Monitoring captures high-resolution sensor data—including selected data—that is time-synchronized via the Precision Time Protocol (PTP) and, depending on the application, is read in via the Connection Modules Vibration (CM VIB), Fast Process Parameters (CM FPP), and IoT (CM IOT). This includes, among other things, vibration data, analog values, and fingerprint information, which are preprocessed locally and then analyzed within the system. The user interface provides plant overviews, KPI trend displays, and detailed diagnostic views that are accessible via a standard web browser. The integrated Industrial AI detects deviations from normal powertrain behavior patterns and provides indications of potential mechanical changes or incipient wear. All data remains within the user’s own infrastructure, as the analytics are performed entirely locally on the industrial PC.

Drivetrain Analyzer Onsite Complements the Existing Cloud Offering

With Drivetrain Analyzer Onsite, Siemens is expanding its drivetrain analytics portfolio for the first time to include a solution for users who prefer purely local data processing. Drivetrain Analyzer Cloud, introduced last year, is designed for cross-system, cloud-based analyses and fleet-wide evaluations. DTA Onsite, on the other hand, is designed for industrial environments where data sovereignty, latency requirements, or isolated network architectures are paramount. Both systems follow the same modular concept but differ in their operating models, integration environments, and regulatory applications. Like Drivetrain Analyzer Cloud, DTA Onsite is also part of Siemens Xcelerator.

DTA Onsite runs on industrial PCs and uses a containerized software architecture. The solution supports open and documented interfaces such as MQTT, gRPC, and OPC UA, enabling integration with SCADA systems, edge platforms, industrial IPC environments, and maintenance software. Data streams from sensors and automation technology are consolidated locally and visualized via a unified monitoring interface.

DTA Onsite Monitoring can be used in a wide variety of industrial environments and is specifically designed for applications with variable load, speed, and operating profiles. These include production machines such as extruders, packaging machines, and textile machines, where mechanical and process-related changes must be detected early on. The function is also suitable for infrastructure applications such as pump stations, compressors, or conveyor lines, which are often operated continuously or within varying load ranges. Motion control systems with dynamic motion sequences also benefit from detailed monitoring, as load peaks and changing operating conditions are systematically recorded and analyzed.

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