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.
Capture and Use Operational Events
Various inbound events such as weather, raw material changes, or equipment modifications can impact production performances. Process conditions can also lead to unwanted outbound events such as equipment failures, fouling, or energy inefficiencies.
Capturing and combining event data with time series analytics is the first step to shedding light on the intricate relationships between process behavior and the context around it. Smaller events may stay unrecognized, but still can have an impact on product quality, cycle time, or any other parameter that lead to your desired production output. Events can be automatically captured, or manually recorded, but are only valuable when they can be used.
Contextualization Enables Smarter Analytics
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 attending this webinar you will:
- Learn how to automatically and manually capture production events.
- Get practical examples on how to use context to speed up Root Cause Analysis.
- 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.
More Reasons to Attend
Can’t attend at this time?
Even if you cannot attend, please do register anyway. We will email you the recorded version after the event so that you can view the webinar at a more convenient time.