The 2017 Industrial Internet of Things (IIoT) Webcast Series

IIoT Webcast Three: IIoT transforms predictive maintenance

One (1) Certified Professional Development Hour (PDH) available for all attendees.

Manufacturers exploiting the latest IIoT industrial-connectivity and analytics advances are melding operations and maintenance data to spot trends that lead managers to contextualized, actionable insights. At the same time, they are building the plant-floor technology infrastructure of the future. Connecting complex machinery and equipment to operations and enterprise systems enables machine learning, predictive maintenance and secure monitor and alarm. IIoT addresses significant integration challenges posed by the unique data types generated by the many kinds of machinery and equipment found in plant environments, from CNC machines to robotics.

Tune into this Webcast to learn how emerging technologies, including IIoT, are leading to business re-engineering, including:
  • Emerging predictive-maintenance models and applications 
  • Incorporation of machine learning and artificial intelligence
  • New cultural and organizational opportunities 
  • A strategic approach to reliability in a real-time world
Speaker: Dave Reiber, CRL/CMRP, Senior Reliability Leader,

Event Sponsors: Bosch Rexroth, Deublin, GTI Spindle Technology, Oracle + NetSuite, Rittal
IIoT Webcast Four: Preventive maintenance: technologies, applications and business models

One (1) Certified Professional Development Hour (PDH) available for all attendees.

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.

Presenter: Alex West, Principal Analyst, Smart Manufacturing & Industrial Communications, IHS Technology

Sponsors: Kepware, Oracle + NetSuite
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