smart plastics - igus Blog - Page 6

Category: smart plastics

What is “Internet of Things/IoT”?

igu-blog-adm | 7. July 2019

Networked machines that communicate independently with each other without the influence of humans are described by the term “Internet of Things”. An illustrative example: The refrigerator, which, via sensors, detects that there is no milk left or a predetermined minimum quantity has been reached, and orders a replenishment at the connected supermarket using a network. […]

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What is predictive maintenance?

igu-blog-adm | 7. July 2019

Predictive maintenance means not too early, not too late, ideally planned and accompanied by the sensible use of human resource. Prescribed maintenance intervals may be too late due to more intensive use of a machine and the equipment might already be on the verge of failure. Too early maintenance, on the one hand, may send […]

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Do we have to let igus on our corporate network?

igu-blog-adm | 6. July 2019

To align sensor data with the igus cloud, you do not need to connect to the corporate network. The modules icom and icom. plus send their data independently via an IoT connection to the igus cloud, and corporate data are not queried at any time. Vote Up +0 Vote Down -0You already voted!

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There are two modules for predictive maintenance, which one do I take?

igu-blog-adm | 5. July 2019

Whether you use the icom or the icom. plus in your plant monitoring depends on how much of the acquired sensor data you want to incorporate in your infrastructure. Before use both modules are initially recorded with the expected trouble-free runtime. This is determined from several parameters such as application area, ambient conditions and operating […]

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How does the maintenance system know that a component should be replaced?

igu-blog-adm | 5. July 2019

The prerequisite for the most accurate information possible on the trouble-free running time of our components is that the details of use given by the operator are accurate. This includes information on the place of use with weather conditions and temperatures, distances, loads, number of cycles, etc. How can we make predictions with these details? […]

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