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Context modeling with situation rules for industrial maintenance

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA)
PublisherIEEE
Pages1-9
Number of pages9
ISBN (Electronic)978-1-5090-1314-2
DOIs
Publication statusPublished - 7 Nov 2016
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Emerging Technologies and Factory Automation -
Duration: 1 Jan 2014 → …

Publication series

Name
ISSN (Print)1946-0740

Conference

ConferenceIEEE International Conference on Emerging Technologies and Factory Automation
Period1/01/14 → …

Abstract

Industrial maintenance requires not only experienced service personnel to carry out the tasks but also up-to-date information about the target equipment and its environment. Accessing information required to execute the tasks is a common challenge for maintenance personnel. This paper presents a knowledge modeling approach and a technical architecture of a gateway system developed to support maintenance personnel with information combined from legacy data sources as well as from context ontology augmented with situational knowledge. The novelty of the approach is its unified object oriented style of knowledge representation encapsulating predefined queries and rules into ontology classes. The approach utilizes standard Semantic Web technologies, especially SPARQL query language and SPARQL Inferencing Notation SPIN. Feasibility of the approach is demonstrated with a simple maintenance use case example executed in an experimental knowledge gateway system.

Keywords

  • internetworking, knowledge representation, maintenance engineering, object-oriented methods, ontologies (artificial intelligence), personnel, production engineering computing, query languages, query processing, semantic Web, software maintenance, SPARQL Inferencing Notation SPIN, SPARQL query language, context modeling, context ontology, gateway system technical architecture, industrial maintenance, knowledge gateway system, knowledge modeling approach, legacy data source, maintenance personnel, predefined query encapsulation, situation rule, situational knowledge, standard Semantic Web technologies, target equipment, unified object oriented style, Cognition, Computational modeling, Context, Context modeling, Maintenance engineering, Object oriented modeling, Ontologies

Publication forum classification

Field of science, Statistics Finland