A new cloud-based end-to-end predictive maintenance solution for rotating equipment from SKF and Amazon Web Services (AWS) is said to be simple, scalable and cost-effective,

SKF Connected Technologies manager John Storm says SKF Axios is an innovative automated equipment monitoring system that trends users’ machine data, detects anomalies around the clock, and sends alerts when action is required.

As the system is always on, it is regarded as the first line of defence to safeguard machinery. Critical information is available at the click of a button as condition monitoring data and alerts can be accessed on any smart device, with specially developed applications providing users with access to data and notifications about anomalies.

The solution applies fully automated wireless technology for three-axis vibration and temperature data collection. Wireless sensors collect data from a range of machinery, the data is analysed and notifications on the health of machinery are then provided. Gateways transfer the data to the Cloud by means of Wi-Fi or ethernet connection.

System alerts are sent to the user when abnormal machine conditions or anomalies are detected, enabling proactive maintenance which helps prevent machine failures, improves productivity and saves costs.  

Storm explains that AWS Cloud Services uses machine learning to analyse data and that historical trend data is the basis for machine learning, so the more data the system collects, the smarter the machine learning becomes, leading to more accurate machine anomaly detection.

The SKF Axios system is designed to be easy to install and is also scalable, allowing users to add sensors and gateways as required.

SKF Axios can be used in a range of industries, including food processing, pulp and paper, pharmaceutical, utilities, tertiary institutions, and medical facilities.