It’s a fact that predictive maintenance and services has, out of the box, proven to be the most significant industrial internet of things (IIoT) application.
What IIoT-based predictive maintenance and services means is that an equipment supplier can assume greater responsibility for the condition of its equipment in the field, and a plant manager can monitor key points in production for integration with enterprise systems.
In either case, we’re talking about use of real-time machine data and analytic models to determine equipment health. The knowledge gained allows convenient scheduling of corrective maintenance that prevents unexpected equipment failures.
Real-time data, connectivity and analytics use supports business models that increasingly rely on 3rd-party services rather than in-house resources.
We’re headed toward a world where real-time device-telemetry collections will integrate with predictive models generated by machine learning, with the model’s “findings” presented via dashboards and visualizations. Tune into this webcast to hear more about it.