Predictive maintenance turns from an art to a science

Published:  07 March, 2017

It’s a challenging problem to accurately predict reliability with limited data. That’s why over the years igus has built up a large database of life calculations and other engineering information about the performance of its bearings, cables and energy chains in various applications.

“Recently, we’ve seen a market trend towards the Internet of Things [IoT] or Industry 4.0”, says Matthew Aldridge, managing director at igus. “igus is supporting its customers in this move and transition by adding intelligence to its products through smart plastics.”

By embedding sensors into its products, igus unlocks the power of IoT to continuously monitor the performance of its bearings, cables and energy chains in real-world customer applications. Comparing live data with the igus test data, igus can accurate predict the lifetime of its products in the field. “No longer is maintenance an art,” says Aldridge, “it’s a science.”

Being able to predict when maintenance is required on a machine, almost eliminates the risk of unplanned downtime. In the automotive industry, for example, unplanned downtime can cost upwards of £10,000 potential profit loss per minute. For port, shipyard and container handling cranes, unplanned downtime can be extremely costly in terms of lost productivity.

“igus smart plastics is not an idea or concept, it’s real products with existing applications in the UK,” asserts Aldridge.

To find out more watch this short video at:

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