18 Oct 2024
WEG (UK) LTD

WEG Agrees Collaborative Partnership

WEG HAS AGREED TO FORM A collaborative partnership with Applied Maintenance Technology (AMT) to promote and use its wireless WEGscan monitoring system in the UK. Conditionbased monitoring and predictive maintenance specialists, AMT, will work closely with WEG to bring this innovative technology to a wider market, enhancing maintenance strategies and operational efficiencies in industrial processes.

WEGscan is a cutting-edge sensor that enables predictive maintenance on a range of industrial equipment, designed to extend lifespans and increase system availability in a cost-effective way. This performance monitoring solution ensures operational excellence through real-time monitoring and predictive maintenance of the industrial drive fleet, significantly reducing the risks of unplanned downtime.

Now in its second generation, WEGscan outperforms competing products in the marketplace with enhanced technical specification, sensor performance, battery life and analytical software tools. This cloudbased solution uses Bluetooth 4 sensors communicating with IP66 rated gateways as internet access points. Each gateway can support approximately 40 sensors with an impressive 100m line of sight wireless range. Gateways connect to the internet via a SIM card and dongle. Users connect to the WEG Motion Fleet Management (MFM) software platform via a web browser with unique username and password access.

Optimised for motors, the system is suitable for any rotating element machine. Relevant bearing numbers can be input or selected from the software library and the machine can be configured accordingly. Simple information is presented on a measurement dashboard for non-professional users, while analysts can access a vibration measurement section with analysis suite, to carry out in depth reviews as required.

Wideband frequency range to 13.5 kHz in all three monitoring planes, allows the sensor to measure vibration in three different directions simultaneously, enabling effective bearing fault identification. This occurs at an early enough stage to prevent catastrophic failures and avoid costly breakdowns. Reliable signal strength, combined with overall readings collected in five-minute intervals are perfect for fault alarm indication. Daily notification reports identify alarm conditions to the user, indicating undesirable equipment conditions.

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