Title
Model-based causal reasoning for process supervision
Abstract
This paper presents the activity of complex process supervision in terms of reasoning: to observe, to validate, to decide, to act, such are the human activities in control rooms. In order to build a system which helps operators in making their decisions, their different tasks are first analyzed, decomposed and shown to rise from causal reasoning. A model-based approach for causal reasoning is then emphasized; the specifications for the model are detailed. An implementation based on a signed directed graph representing causality, and on simple transfer functions describing the propagation of information through the graph, is finally proposed. The capacities of this modelling method to simulate, to explain and to give action advice are demonstrated on an industrial example.
Year
DOI
Venue
1994
10.1016/0005-1098(94)90109-0
Automatica
Keywords
Field
DocType
process supervision,model-based causal reasoning,transfer function,personnel management,simulation,artificial intelligent,supervisory control,artificial intelligence,directed graph,nuclear reactor,control system,causal reasoning
Human resource management,Causal reasoning,Causality,Computer science,Supervisory control,Directed graph,Model-based reasoning,Operator (computer programming),Process control,Artificial intelligence
Journal
Volume
Issue
ISSN
30
8
0005-1098
Citations 
PageRank 
References 
12
1.89
7
Authors
3
Name
Order
Citations
PageRank
Lydie Leyval1182.62
Sylviane Gentil28911.94
Stéphane Feray-Beaumont3121.89