A Digital Plant Template example.
These operational insights are generated automatically using PI Analytics and Event Frames. All process units for an industrial complex are evaluated for their operating modes. These are based on the production variance, which is calculated from the scheduled production and actual performance using PI Analytics. The operating modes are used to estimate the production and operating cost losses similar to an OEE strategy but much more powerful.
The results are visualized using PI Vision and Microsoft PowerBI with Cortana (Artificial Intelligence). In addition, it provides the necessary data for developing machine learning predictive analytics using Excel with PI Datalink and Analysis ToolPack add-ins, Microsoft Machine Learning (ML) Studio, or Anaconda Python.
In the last part of the session, based on the current industrial practice, implementation tips are provided for the students to implement for their own use. The Academia-Industry students will get the Digital Plant Vision Template in a PI Asset Framework XML file template, PowerBI Template, PI DataLink Template data classification and multilinear regression, and the ML Studio step-by-step processes to get the extracted data into a multilinear regression model.
The example simplifies the implementation and adoption of the latest data science technologies. It takes less than hour to the get the plant simulator configured and running.
After it is running as simulation, it can be re-purpose and configured with real tags.
This is good stuff. Thanks for sharing!