Easy to install and battery powered, the IMx-1 sensors form a scalable network to collect a range of health data from your rotating assets. Large volumes of plant asset data can then be automatically interpreted by SKF Enlight AI machine learning and expert fault verification systems. Results are displayed in easy to understand SKF Enlight Centre dashboards, and can be uploaded to the SKF Cloud and connected to SKF Rotating Equipment Performance (R.E.P) Centres where SKF application experts can provide further advice as required. Automated monitoring frees up engineers who no longer need to complete walk-arounds, and automated data interpretation and expert fault verification systems allow you to interpret large volumes of machine data, giving you valuable insights into your rotating equipment performance.
As the Industrial Internet of Things continues to grow, plants can take advantage of a range of exciting new technologies that can not only improve performance and reliability, but also free up skilled workers to focus on important tasks. One such example is the scalable SKF Enlight Collect IMx-1 that creates an easy to set-up mesh sensor network to collect data on rotating components. We sat down with Chris James, Product Line Manager at SKF Group to learn how and why the IMx-1 was created and find out what future developments SKF have planned.
SKF fee and performance-based contracts. A new way of achieving and paying for maintenance and reliability. Watch the video to discover how to approach machine management in a new way. Or find out more about our innovative approach to Rotating Equipment Performance.
As a chemical company, safety is of the highest importance for BASF, as their production processes must comply with safety regulations including having online condition monitoring systems on all critical applications as standard.
BASF had been looking at condition monitoring systems with wireless sensors for critical and semi-critical applications for a long time due to their practicality in both cost and ease of installation.