Collaboration produces automated condition monitoring system

A new condition monitoring solution which claims to reinvent the fields of industrial machine reliability and predictive maintenance has been launched following a collaboration between bearings specialist SKF and Amazon Web Services.

SKF Axios is a fully automated condition monitoring system – exhibited during Hannover Messe 2022 earlier this month – which its developers say allows manufacturers to use simple and affordable wireless technology to monitor more equipment in their facilities.

The solution is comprised of sensors, gateways and a machine learning service that is easy to install, commission, and scale. It detects anomalies and pushes notifications, supporting quick decision making to avoid unexpected machine failures and allowing firms broaden their rotating asset predictive maintenance programs.

“With SKF Axios, we are able to provide a larger portion of the industrial market with actionable insights leading to improved decision making and more efficient maintenance planning and scheduling,” said SKF’s President, Industrial Region Americas, John Schmidt.

“Through leveraging these insights and SKF’s knowledge of rotating equipment, customers can improve machine performance and overall reliability of their operations.”

Inventory for SKF Axios is expected to be available July 2022 in North America with other regions expected to follow throughout the year.

AWS Vice President of AI Services Vasi Philomin said: “SKF Axios represents a tremendous opportunity for industrial customers of all sizes to benefit from scalable, data driven, machine learning technologies offered by AWS.

“These solutions enable industrial customers to make better decisions faster, increasing operational efficiency, and reducing the costs associated with unplanned equipment downtime. We remain committed to offering our expertise in cloud solutions, IoT systems, and machine learning to enable SKF to constantly innovate and enhance their industrial products and services.”