Igus introduces the next generation of intelligent cable

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At the heart of every intelligent cable from igus is a complex sensor called CF.Q. With the module, the electrical properties can be tested in additional measuring cores and continuously compared with existing empirical values of a given chainflex cable. Damage by bending or extreme loads can be reliably detected. In addition, guide values for the cables can be defined in advance. If the CF.Q module is installed, it informs the customer by actuating a normally closed contact when these predefined values of the electrical parameters change. Only the combination of empirical values and real-time measurement allow users precise maintenance predictions for their cables – especially in the dynamic production environment. This is made possible by an industry 4.0-capable application called isense-online. It compares the recorded real-time values of the cable and the empirical values existing in a database, and if it detects fluctuations, it prompts the plant operator to initiate maintenance. And this is indeed done before the damage occurs and the production or plant shutdowns become a risk.

The new generation of CF.Q modules are now suitable for switch cabinet assembly thanks to top-hat rail housings and thus offering additional flexibility for electrical engineers in terms of integration as well as handling. In addition, the modules are suitable for data logging thanks to the SD card slot. An output of the measured values on a serial interface is also integrated as standard. Customers who want to get a precise insight into the recorded measured values can do so by connecting to the isense-online system via a detailed view. In any case, the user has access to a wide variety of communication channels and reporting options.

Maintenance recommendations or impending failures are displayed in the classic browser view of desktop PCs, as well as on all mobile devices such as tablets and smart phones. For maintenance teams and production managers, intelligent igus cables are bringing in a paradigm shift in maintenance and servicing through accurate prediction.

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