• Welcome

Siemens and Schaeffler collaborate on intelligent diagnosis of drive systems

Blog 3年前 (2021-08-17) 359 Views

Original title: Siemens and Schaeffler collaborate on intelligent diagnosis of drive systems

Gasgoo Automotive News On May 11, Siemens cooperated with auto parts supplier Schaeffler to conduct intelligent diagnosis of the drive system. Through this cooperation, Siemens will combine its IIoT (Industrial Internet of Things) platform Sidrive IQ with Schaeffler's decades of experience and expertise in bearing design, manufacturing and maintenance. Sidrive IQ integrates many functions into a seamless solution and enhances the drive system with AI-based analysis and digital content.

Siemens and Schaeffler collaborate on intelligent diagnosis of drive systems

(Image source: Siemens)

This solution can help customers make better decisions on the operation, maintenance and repair measures of the drive system. Electric motors drive our core industrial processes, and rolling bearings are the core mechanical components. The bearing bears all loads and stresses that occur in the motor. Therefore, bearing diagnosis can provide key indicators for the overall condition and reliability of the motor. Schaeffler's automatic bearing diagnostic analysis service is integrated with Sidrive IQ to more accurately determine the condition of the bearing.

Hermann Kleinod, CEO of Siemens Large Drive Applications, said: "This collaboration and automatic exchange of algorithm-based diagnostic data is the first case in the field of IIoT, and it is also a successful case of cooperation with established technology companies in new fields."

Dr. Stefan Spindler, CEO of Schaeffler Industries, said: "This cooperation is based on product knowledge and specific expertise. Schaeffler and Siemens will focus on customer value and continue to promote the digital development of the industry."

With a wealth of insight and specific information, operators can quickly determine whether the drive system can continue to run, or in the event of impending damage, whether the bearing needs to be replaced at the next maintenance interval, or whether to replace the bearing immediately. This approach can reduce maintenance workload and maintenance costs, and most importantly, can prevent unplanned and costly downtime.