Authors:
Qiushi Cao
1
;
Cecilia Zanni-Merk
1
and
Christoph Reich
2
Affiliations:
1
Normandie Université, INSA Rouen, LITIS, 76000 Saint- Étienne-du-Rouvray and France
;
2
Hochschule Furtwangen University, 78120 Furtwangen and Germany
Keyword(s):
Industry 4.0, Condition Monitoring, Preventive Maintenance, Ontology, Intelligent System.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
In the manufacturing domain, machinery faults cause a company high costs. To avoid faulty conditions, the discipline of condition monitoring contributes significantly. The objective of condition monitoring is to determine the correctness of a machine, process or system. This is crucial for improving the productivity and availability of production systems. In most situations, when the tendency of a fault emerges, highly experienced and skilled professionals are capable of providing appropriate decisions about fault alarm launching and maintenance plans. However, production systems are becoming more complicated, and it is more likely that the professionals fail to respond to the faulty conditions timely and accurately. In this paper, we present an ontological framework, that is used for developing an intelligent system, which can provide decisions about alarm launching and maintenance plans in an intelligent and optimal manner. This framework is based on an ontological representation o
f condition monitoring knowledge in the manufacturing domain. The framework consists of an ontology structure which includes a core reference ontology for representing general condition monitoring concepts and relations, and several domain ontologies for formalizing manufacturing domain-specific knowledge.
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