Webinar on Demand
Operating in the Fast Lane
Contextualize Time-Series Data for Smarter Analytics
Duration: 45 minutes
In the world of IIoT, data is considered to be the new oil. But the full potential will only be unleashed if the operational context can be taken into account when analyzing, monitoring or predicting operational performance. Shedding necessary light onto time-series data through dynamic contextualization enables you to take your processes into the highest gear of operational excellence, and your organization into the future.
In this webinar we will introduce the analytical benefits of combining time series sensor data with contextual data. You will see how you can use captured events as a starting point to continuously improve your production facilities.
By watching this webinar you will:
- Learn how to automatically and manually capture production events.
- Get a practical example on how to use context to speed up Root Cause Analysis of mechanical failures
- Gain insights into how context stored in 3rd party data silos can be used most effectively.
- Leverage context for data driven decisions in the control room
- Build a self-learning organization by automatically capturing events.
Nick is a chemical engineer whose passion is solving problems through collaboration and data driven decision making. As a Data Analytics Engineer at TrendMiner, Nick draws on his extensive experience in manufacturing and data analytics to lead customers through use case resolution.
Nick holds a Bachelors of Science in Chemical Engineering from the University at Buffalo. Between 2011 and 2018 Nick worked as a Technology Engineer at BASF Corporation. Nick was responsible for capital projects, process troubleshooting, plant optimization, debottlenecking, automation, and digitalization efforts.