Authors:
Brigitte Chebel Morello
1
;
Mohamed Karim Haouchine
2
and
Noureddine Zerhouni
1
Affiliations:
1
Institute of Automatic Control and Micro-Mechatronic Systems, France
;
2
Em@systec sas, France
Keyword(s):
Case-based reasoning, Adaptation, Adaptation-guided retrieval, Dependency relations, Hierarchical model, Context model, Industrial diagnostic, Diagnostic help system, Industrial diagnostic.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Best Practices & Communities of Practice
;
Communities of Practice
;
Computer-Supported Education
;
Intellectual Capital
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Learning/Teaching Methodologies and Assessment
;
Society, e-Business and e-Government
;
Symbolic Systems
;
Tools and Technology for Knowledge Management
;
Web Information Systems and Technologies
Abstract:
The adaptation phase is a key problem in the design of Case-Based Reasoning (CBR) systems. In most cases, adaptation methods are application-specific. Our challenge in this work is to make a general adaptation method for the field of industrial diagnostics. This paper is a contribution to fill this gap in the field of fault diagnostic and repair assistance of equipment. Our adaptation algorithm relies on hierarchy descriptors, an implied context model and dependencies between problems and solutions of the source cases. In addition, we note that the first retrieved case is not necessarily the most adaptable case, and to take into account this report we propose in our diagnostic problem an adaptation-guided retrieval step based on a similarity measure associated with an adaptation measure. These two measures allow selecting the most adaptable case among the retrieved cases. The two retrieval and adaptation phases are applied on real industrial system called SISTRE (Supervised industria
l system of Transfer of pallets).
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