Drivetrain Analyzer Edge - Drive Analytics

Why Drivetrain Analyzer Edge?

Drivetrain Analyzer Edge is an industrial edge application that provides less downtime and more sustainability for connected systems. It monitors and analyzes your SINAMICS drive data in real time using AI and data analysis models. Gain valuable on-premise insights to optimize your drive systems for productivity, efficiency and sustainability.

Avoid unplanned downtime and lower energy consumption using Drivetrain Analyzer Edge. Continuously monitor and analyze drive data to detect anomalies and potential issues early.

Use AI and data analysis models to gain transparency into energy consumption, operating costs and CO2 footprint without additional sensors. Detect mechanical anomalies by analyzing drive data to enable predictive maintenance. Customize AI models for your specific conditions.

Key benefits

Lower energy consumption and operating costs

Achieve sustainable production with energy-efficient coolant pumps. Record and analyze SINAMICS G120C drive data to extend system life. Reduce operating and investment costs.

Enable predictive maintenance

Remotely monitor packaging machines without extra sensors. Enable predictive maintenance by importing relevant vibration and status variables from SIPLUS CMS1200.

Increase machine availability

Analyze SINAMICS G120 drive data to detect anomalies. Monitor machine conditions to improve maintenance planning. Avoid inefficient machine use and increased energy costs for reliable operation.

Featured capabilities

Siemens DTA Edge Energy Efficiency infographic showing energy savings and efficiency improvements.

Energy transparency monitoring

Gain transparency into your 2nd gen G type SINAMICS drives' energy consumption, operating costs and CO2 footprint. Increase energy efficiency with a model calculating all data without sensors or special equipment.

A Siemens advertisement featuring a customizable AI system with a futuristic design.

Customizable AI model

Create customized AI models according to individual use cases. Visualize the KPIs of user-developed AI models with charts and gauges to analyze specific predefined conditions.

Basic anomaly detection

Visualize calculated basic statistical KPIs for drive parameters, including mean and standard deviation. Monitor long-term degradation and detect anomalies. Gain transparency for systematic variations in drive data KPIs.