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An ontology-based intelligent data query system in manufacturing networks
oleh: Salman Saeidlou, Mozafar Saadat, Ebrahim Amini Sharifi, Guiovanni D. Jules
| Format: | Article |
|---|---|
| Diterbitkan: | Taylor & Francis Group 2017-01-01 |
Deskripsi
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.