ABOUT THIS WEBINAR

Topic: Sensor & IoT Analytics

Intended Audience:

Analytics Managers, Chief Analytics Officers, Heads of Technology Innovation, Industrial Data Scientists, IT/IoT Solution Architects, Chief Technology Officers

Length: 46 minutes

The Industrial IoT (IIoT) is revolutionizing manufacturing and supply chain management through advances in human-machine interaction and decision support. Some benefits of IIoT enabled processes include the use of Machine Learning to optimize operational efficiency, improve productivity, reduce downtime, and maximize asset utilization.

Industrial systems monitor each critical part of a process, often by way of SCADA and telemetry data feeds. The more complex the operating environment, the more sensors are installed and embedded. As sensing devices become cheaper, smaller, and more capable, IIoT-enabled machines provide more data to machine learning algorithms to identify patterns that indicate a future failure, or opportunities for greater efficiency.

Sensors provide critical operational benefits such as:

Warning users and operators of imminent threats

Alerting about depletion of critical resources to improve supply chain efficiency

Enabling real-time and predictive maintenance to improve up-time

But by observing complex patterns in sensor data over extended time periods, Machine Learning can help anticipate problems and opportunities earlier. For example, precisely targeted preventative maintenance reduces downtime and costs, thereby increasing asset utilization and profits. The challenge of managing the large and complex streaming data from IIoT systems can be overwhelming.



Data Scientists Ramon Perez and Will Goodrum will discuss some of the common challenges encountered when working with sensor data, and how we have helped clients in diverse industries find value in the connected data deluge to drive operational efficiency and reduce downtime.



Attendees will learn: