Speaker
Tamas Ruppert
Description
We demonstrate how the toolbox of artificial intelligence (AI) and machine learning (ML) can support the monitoring of processes. We highlight how these functions can be implemented in existing process control systems and how open source solutions (e.g., Python toolboxes) can be goal-oriented tailored for their development.
We give an in-depth overview of the steps of the workflow of the implementation of these solutions and present the structure of an AI/ML supported process control system. The methodology and the results are presented concerning the AI/ML-based improvement of the monitoring and operation support functionalities in the WebSCADA system of an industrial water treatment plant.
Primary authors
Tamas Ruppert
Gyula Dörgő
(MTA PE Lendület Complex Systems Monitoring Research Group)
Prof.
János Abonyi
(University of Pannonia)
