Connecting IoT Data to Digital Workflows Enables True Predictive Maintenance

As the Internet of Things (IoT) continues to gain momentum, it’s no surprise that many industries are looking for new, innovative ways to derive value from incoming data to transform their maintenance operations. But to truly reap these benefits, it’s important to recognise that grabbing as much data as you can from your assets isn’t enough. You need an intelligent platform that can turn this information into action.

Fortunately, there are new technologies to help you do that. A new streamprocessing IoT Bridge evaluates live device data against user-defined rules to automatically trigger digital workflows. These workflows make it possible to collect, view and act upon the large volumes of data streamed from IoT-enabled devices and systems. By combining real-time machine data with predictive algorithms, these workflows can even help you forecast equipment failures before they happen— unlocking the benefits of true predictive maintenance.

This white paper takes a closer look at how IoT technology is making machine data actionable and laying the foundation for predictive maintenance in industrial environments.

 Internet of Things

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