An Ontology-based Intelligent Data Query System in Manufacturing Networks

Salman Saeidlou, Mozafar Saadat, Guiovanni Jules

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
190 Downloads (Pure)

Abstract

This paper investigates the development of an intelligent data query framework through the use of semantic web technologies for manufacturing purposes. The primary objectives of the ontology-based data query were to develop an efficient and scalable data interoperability and retrieval system; in order to find the most relevant query results with minimum message cost, most hits per query and least response time. This document explains the idea of ontology and the application of the same in the manufacturing domain. A computer simulation software was developed based on a real case study of distributed networks of manufacturing workshops. In this research, a semantic query algorithm was developed where query results are returned by investigating the semantic richness of each workshop. Results were compared with a semantic-free search mechanism based on key performance indicators. The results show the validity of the proposed model for efficient data query when compared to random search.
Original languageEnglish
Pages (from-to)250-267
JournalProduction & Manufacturing Research
Volume5
Issue number1
Early online date11 Oct 2017
DOIs
Publication statusPublished - 2017

Keywords

  • distributed systems
  • ontology
  • manufacturing data query
  • data interoperability

ASJC Scopus subject areas

  • Engineering(all)

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