We use PI Integrator to publish the data in a row-column format for the next steps.
And, use PowerBI for descriptive analytics with this large dataset covering several months of minute resolution data.
Next, R is used for more data munging and extract the golden temperature profile.
And, validate the model to confirm if it can flag bad runs using shape metrics.
And, after it is validated, wedeploy it for real-time operations by writing to a PI future tag.
During operation, deviation from the expected temperature profile is continuously evaluated and it triggers a Notification to take corrective action.
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