Predictive Maintenance

Schaeffler and Siemens to cooperate on intelligent diagnostics for drive systems

21 May 2021

Electric motors drive our core industrial processes, and the rolling bearing is their central mechanical component. The bearings experience all of the loads and stresses that occur in the electric motor. Therefore, bearing diagnostics provide a crucial indicator of the overall condition and reliability of a motor.

In addition to developing a portfolio of condition monitoring solutions for operators, Schaeffler is also working with OEM customers such as Siemens on joint offerings to increase the availability of machinery and equipment.

“This partnership between Schaeffler and Siemens is based on a solid foundation of product knowledge and specific expertise. Both companies are playing an instrumental role in driving digitalisation forward in the industry while keeping their entire focus on customer value,” adds Dr. Stefan Spindler, CEO Industrial of Schaeffler AG.

Services seamlessly integrated in one platform 

The collaboration between Siemens and Schaeffler combines Sidrive IQ – the digital platform for drive systems and solutions from Siemens – with Schaeffler’s experience and expertise in designing, manufacturing, and servicing bearings. Sidrive IQ integrates a number of functionalities into one seamless solution and augments drive systems with AI-based analytics and digital content. For the customer, this means the ability to make better decisions when it comes to operation, maintenance, and maintenance measures for drive systems.

New dimensions of collaboration in the Industrial IoT 

The integration of Schaeffler’s analysis service for automated bearing diagnostics in Sidrive IQ makes it possible to determine the bearing condition with greater certainty and precision. “This cooperation and automated exchange of algorithm-based diagnostic data is one of the first of its kind in the industrial IoT. It’s a great example of a new dimension of cooperation among established technology companies,” says Hermann Kleinod, CEO of Siemens Large Drives Applications. 

With the help of well-founded insights and specific information, operators can quickly determine whether the drive system can continue to operate or whether, in the event of impending damage, the bearing needs to be replaced immediately or can wait for the next maintenance interval. This reduces maintenance effort and cost, and most importantly, unplanned and costly downtimes can be prevented.


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Predictive Maintenance

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