Artificial intelligence for industrial process supervision

Authors:
S. Gentil
Affiliations:
Laboratoire d’Automatique de Grenoble, UMR 5528 CNRS-INPG-UJF, Saint Martin d’Hères
Venue:
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Year:
2006

Citing 4
Cited 0

Hierarchical representation of complex systems for supporting human decision making

Advanced Engineering Informatics
Trends extraction and analysis for complex system monitoring and decision support

Engineering Applications of Artificial Intelligence
Combining FDI and AI approaches within causal-model-based diagnosis

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dynamic causal model diagnostic reasoning for online technical process supervision

Automatica (Journal of IFAC)

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents some difficulties of complex industrial process supervision and explains why artificial intelligence may help to solve some problems. Qualitative or semi-qualitative trend extraction is mentioned first. Then fault detection and fault supervision are evoked. The necessity for intelligent interfaces is explained next and distributed supervision is finally mentioned.