Industry 4.0 - igus Blog - Page 4


Industry 4.0

Smart Factory Summit 2021: my personal review and classification

Richard Habering | 1. October 2021

How do OEMs and automotive suppliers network their production plants? What can SMEs, especially the mechanical engineering sector, do to make their manufacturing smart and efficient? What role do the suppliers play? How can artificial intelligence help make production smarter?These and other questions were presented this week at the Smart Factory Summit of the Deutsche Messe Technology Academy and explained by numerous expert speakers. Among the select field of participants were the companies KUKA, SEW Eurodrive, Siemens, Yaskawa and also us from igus.


Why wait? More time for important things thanks to smart maintenance

Richard Habering | 16. September 2021

In the current climate, every minute often counts in production plants. Efficient, intelligent maintenance protects against expensive production downtimes and unplanned shutdowns. The service life of our igus® products can be calculated online. What's more: With smart plastics, the components report at an early stage when they are due for replacement. In this article I would like to show you how we have successfully introduced smart maintenance to our customers.


Smart factory: intelligent plant monitoring with the FANUC FIELD system and igus smart plastics

Richard Habering | 31. August 2021

For machine data evaluation in the smart factory, FANUC offers the "FIELD system" industrial IoT platform. igus is also involved with its i.Cee app for predictive maintenance.


Talking energy supply system on a crane

Richard Habering | 6. August 2021

Why should an energy supply system talk to me? Maintenance and servicing for current crane systems is growing not only in size, but also control complexity. But there is no need to panic because, as you learned during your studies, you don’t need to know everything; you just need to know where to find the […]


“Data is the new oil” – How the igus test laboratory generates raw data that drive all smart plastics products

Richard Habering | 28. July 2021

Anyone who can make reliable, useful maintenance predictions is one step ahead of the competition. In the age of digitalisation, more than Big Data is required for such predictions. To derive correct maintenance scheduling recommendations from the sensor data, we therefore compare them with long-term empirical values from the igus® test database.