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Fit for Purpose - Layers of Analytics using the PI System - Part 3

Blog Post created by gopal on Jan 24, 2020

We use PI Integrator to publish the data in a row-column format for the next steps.

 

Feed Dryer PI Integrator output

 

And, use PowerBI for descriptive analytics with this large dataset covering several months of minute resolution data.

 

Feed Dryers - Power BI  screen

 

Next, R is used for more data munging and extract the golden temperature profile.

 

Feed Dryer Golden Temperature Profile

And, validate the model to confirm if it can flag bad runs using shape metrics.

 

Feed Dryer Shape is not OK

 

And, after it is validated,  wedeploy it for real-time operations by writing to a PI future tag.

 

Feed Dryer Operationalize expected temperature profile

 

During operation, deviation from the expected temperature profile is continuously evaluated and it triggers a Notification to take corrective action. 

Feed Dryer Notification

 Feed Dryer PI Vi

 

 

Go to Part 1

Go to Part 2

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