SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
Open Access
- 29 July 2021
- journal article
- research article
- Published by MDPI AG in Information
- Vol. 12 (8), 304
- https://doi.org/10.3390/info12080304
Abstract
This paper introduces the Steel Cold Rolling Ontology (SCRO) to model and capture domain knowledge of cold rolling processes and activities within a steel plant. A case study is set up that uses real-world cold rolling data sets to validate the performance and functionality of SCRO. This includes using the Ontop framework to deploy virtual knowledge graphs for data access, data integration, data querying, and condition-based maintenance purposes. SCRO is evaluated using OOPS!, the ontology pitfall detection system, and feedback from domain experts from Tata Steel.Keywords
Funding Information
- Engineering and Physical Sciences Research Council (EP/T517537/1, EP/S018107/1)
This publication has 23 references indexed in Scilit:
- Efficient SPARQL-to-SQL with R2RML mappingsJournal of Web Semantics, 2015
- The protégé projectAI Matters, 2015
- RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data IntegrationPublished by Springer Science and Business Media LLC ,2015
- OOPS! (OntOlogy Pitfall Scanner!)International Journal on Semantic Web and Information Systems, 2014
- Ontology-based supply chain decision support for steel manufacturers in ChinaExpert Systems with Applications, 2013
- ONTO-PDM: Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environmentAdvanced Engineering Informatics, 2012
- Survey of directly mapping SQL databases to the Semantic WebThe Knowledge Engineering Review, 2011
- Ontology Design PatternsPublished by Springer Science and Business Media LLC ,2009
- Web Ontology Language: OWLPublished by Springer Science and Business Media LLC ,2004
- Life of rolls in a cold rolling mill in a steel plant-operation versus manufactureEngineering Failure Analysis, 2000