“I.Cee:local”: from Igus, a new module for predictive maintenance

A new smart module that predicts the operating life of machinery and equipment. It’s “I.Cee:local”, the new module created by Igus, the German motion plastics specialist, to optimize the use of equipment, capable of detecting and correcting anomalies very quickly, so as to plan an efficient maintenance of cable carriers, cables, linear guides and bearings during operation, helping maximize the use of components and minimize management costs and waste.

The service life forecast, which we determine on the basis of millions of test data in our in-house 3,800 square meter laboratory, is compared and adjusted during operation with the values actually determined, so that a real-time service life statement can be made about the durability of the machine and system,’’ said Richard Habering, Head of the smart plastics Business Unit at igus GmbH.

While “smart plastics” sensors monitor abrasion, measure the pull/push force and provide information about an imminent overload, the i.Cee:local solutions allow maintenance managers to receive information about the condition of the “smart plastics” systems in real time. The data of the “i.Cee:local” sensor can be accessed either via a display on the system, via a cloud solution or an IoT dashboard, such as Json/Mqtt protocol, on the intranet, via the Rest Api interface or directly via SMS or email, offline or online.
Furthermore, it is the home of the open source software “i.Cee” and the brain of the smart plastics, showing one of the key features of the new module: multi-connectivity. The possibility of seamless integration into the designated network environments allows the implementation of various Industry 4.0 use cases.

Depending on the customer’s requirements – said Richard Habering – the data can be accessed quickly and easily by the maintenance staff, thanks to the i.Cee:local sensor“.

“I.Cee:local”: from Igus, a new module for predictive maintenance ultima modifica: 2021-11-15T13:37:23+00:00 da Francesco Inverso