The Industry 4.0 era calls for a rethink of traditional processes in quite a number of areas. One example is using predictive maintenance based on continuous condition monitoring rather than checking machine tools at fixed intervals. These tools then only need to undergo maintenance or be replaced when the system signals this is necessary. Comparing status data with target parameters on an ongoing basis also measurably reduces unscheduled stoppages and therefore downtime costs. igus GmbH has achieved these benefits by using smart plastics to develop various sensors and monitoring modules for everything from energy chains and cables to plain, linear and slewing ring bearings. Networking these products with the new igus communication module (icom.plus), which igus is soon to showcase at the upcoming EMO Hannover 2019, ensures direct integration into the customer’s own IT infrastructure – into production management systems such as SCADA and MES, for instance, or online into cloud solutions that are used throughout a company.
Once programmed with initial service life algorithms using igus online configurations, icom.plus can also be operated offline if the customer wishes. This gives users flexibility when it comes to decisions about how the module is connected, how its data is managed and how to balance run time maximization against IT security. As long as icom.plus is online, the service life data is continuously compared with the igus cloud to maximize machine run times and minimize the risk of a failure. The data in the cloud includes details of the ten billion energy chain and cable test cycles performed each year in the company’s own 3,800 square meter test laboratory. Based on this data, it is possible to predict with impressive accuracy how long a component such as an energy chain will work reliably in the respective machine tool application. Integrated isense components that factor in the current ambient conditions provide additional reassurance by continually updating the service life. Machine learning and AI produce extremely precise data that can be viewed on the machine control system’s screen. If users opt for online connection, a text message or e-mail is also sent to notify them of unexpected operating states and scheduled maintenance.