Maintenance in the age of Industry 4.0 represents a clear paradigm shift. Instead of completing fixed maintenance intervals and merely reacting to a failure or malfunction, predictive maintenance enables continuous condition monitoring of the machine tool. Maintenance and replacement only takes place when it is really necessary. Maintenance work can be planned precisely. At the same time, unplanned downtimes and therefore downtime costs are reduced thanks to permanent measurement.

To make this possible, Igus has developed various sensors and monitoring modules for energy chains, cables, plain, linear and rotary table bearings with smart plastics. For example, sensors for measuring the abrasion or wear of the pin-bore connection of energy chains as well as sensors for detecting breakage and tensile shear force.

Networking with the Igus Communication Module plus (icom.plus), which Igus will be exhibiting at Emo, enables direct integration into the customer's IT infrastructure, for example into production management systems such as Scada and MES or online into company-wide cloud solutions.

Flexible data integration
icom.plus is programmed via Igu's online configurations with initial lifetime algorithms and can be operated offline after online installation without an update function at the customer's request. This allows the user to design the connection of the module and thus its data and strike a balance between runtime maximization and IT security.

When the icom.plus is connected online, the service life statement is continuously compared with the igus Cloud to ensure maximum machine running times with minimum risk of failure. Among other things, the data in the cloud draws on the data from the ten billion test cycles of energy chains and cables carried out annually in the company's own 3,800 square meter test laboratory. Based on these tests, which are fed into the freely available online service life calculators, it is possible to predict quite accurately in advance how long an e-chain, for example, will work reliably in the respective machine tool application.

The Isense components provide the customer with additional security through a permanent service life update. This is because it takes into account the current environmental conditions of the running application. Thanks to machine learning and AI, precise information on the service life of the individual solutions used in the actual running application is possible. This information can be viewed on the system control screen, and if an online connection is selected, an SMS or email also informs the customer if unexpected operating states occur or maintenance is due. as