On a Uniform Causality Model for Industrial Automation

• URL: http://arxiv.org/abs/2209.09618v1
• Date: Tue, 20 Sep 2022 11:23:51 GMT
• Title: On a Uniform Causality Model for Industrial Automation
• Authors: Maria Krantz, Alexander Windmann, Rene Heesch, Lukas Moddemann, Oliver Niggemann
• Abstract summary: A Uniform Causality Model for various application areas of industrial automation is proposed. The resulting model describes the behavior of Cyber-Physical Systems mathematically. It is shown that the model can work as a basis for the application of new approaches in industrial automation that focus on machine learning.
• Score: 61.303828551910634
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The increasing complexity of Cyber-Physical Systems (CPS) makes industrial automation challenging. Large amounts of data recorded by sensors need to be processed to adequately perform tasks such as diagnosis in case of fault. A promising approach to deal with this complexity is the concept of causality. However, most research on causality has focused on inferring causal relations between parts of an unknown system. Engineering uses causality in a fundamentally different way: complex systems are constructed by combining components with known, controllable behavior. As CPS are constructed by the second approach, most data-based causality models are not suited for industrial automation. To bridge this gap, a Uniform Causality Model for various application areas of industrial automation is proposed, which will allow better communication and better data usage across disciplines. The resulting model describes the behavior of CPS mathematically and, as the model is evaluated on the unique requirements of the application areas, it is shown that the Uniform Causality Model can work as a basis for the application of new approaches in industrial automation that focus on machine learning.

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