Increase plant safety, reduce maintenance costs with smart plastics from igus

New intelligent plastic solutions offer many options for predictive maintenance.

The smart plastics increase plant reliability by the accurate prediction of their service life. This is especially useful, for example, when a large number of e-chains are used in production.

Machine Learning, Big Data and Industry 4.0 – the real potential customer benefits from digitisation are often hidden behind these buzzwords. Intelligent products such as igus smart plastics, for example, enable companies to increase the reliability of their systems, plan maintenance tasks accurately and thus save costs. The way this works was demonstrated by igus with new ideas at the Hannover Messe 2018.

igus has been developing a family of products since 2016 under the heading ‘isense’, where various sensors and monitoring modules add intelligence to plastic solutions such as energy chains, cables, linear guides and slewing ring bearings. They measure among other things the wear during the operation and alert the user early enough to plan repair or replacement. By networking using the igus communication module (icom), the online status and alert display, for example via a PC, tablet or smartphone, is just as possible as a direct integration into the customer’s infrastructure. These smart plastics are already predicting the service life of numerous customer applications, such as in the automotive industry. They are continuously developed in close cooperation with customers. These novelties were presented by igus at the Hannover Messe.

Individual integration of smart plastics

The improved isense modules, which use sensors to collect data from the energy chain, cable, linear guide or slewing ring bearing, are equipped with a serial interface and can be easily integrated into a control cabinet. A data logger allows the storing of values on an SD card. The data measured by the different isense systems are then sent wirelessly to the icom module, summarised and processed. The customer has the choice of various concepts for integration into their own infrastructure. In this way there is an option for the icom to send the data from the sensors to a PC or integrate the data via the computer into the existing software environment and intranet solution. In addition, a connection to the igus Data Center is possible. In this case, the maintenance recommendations via Machine Learning and AI algorithms are constantly compared and defined with the experiences of many existing applications, for example in the large igus test laboratory spread over a floor area of 2,750 square metres.


For more details, visit www.igus.in

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