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SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0

Sadeer Beden, Qiushi Cao, Arnold Beckmann Orcid Logo

Information, Volume: 12, Issue: 8, Pages: 304 - 18

Swansea University Authors: Sadeer Beden, Qiushi Cao, Arnold Beckmann Orcid Logo

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DOI (Published version): 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 us...

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ISSN: 2078-2489
Published: MDPI AG 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa57654
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first_indexed 2021-08-18T22:06:10Z
last_indexed 2023-01-11T14:37:43Z
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spelling 2022-07-05T15:33:58.5237581 v2 57654 2021-08-18 SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0 acf0be82092335f6fb65bb51f29c46ac Sadeer Beden Sadeer Beden true false 5c00afca4cb5fa62e43bda660a1a27b5 Qiushi Cao Qiushi Cao true false 1439ebd690110a50a797b7ec78cca600 0000-0001-7958-5790 Arnold Beckmann Arnold Beckmann true false 2021-08-18 SBI 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. Journal Article Information 12 8 304 18 MDPI AG 2078-2489 Industry 4.0; steelmaking; cold rolling; ontology; Ontop 29 7 2021 2021-07-29 10.3390/info12080304 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) EPSRC. S. Beden was supported by the Engineering and Physical Sciences Research Council (grant number EP/T517537/1) and by Tata Steel. Q. Cao and A. Beckmann (in part) were supported by the Engineering and Physical Sciences Research Council (grant number EPSRC EP/S018107/1). EP/T517537/1, EP/S018107/1 2022-07-05T15:33:58.5237581 2021-08-18T22:36:20.2361714 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Sadeer Beden 1 Qiushi Cao 2 Arnold Beckmann 0000-0001-7958-5790 3 57654__20955__200563c34ab6447ca6ff5d65dcdf7eed.pdf 57654.pdf 2021-09-21T13:39:37.1048456 Output 6848770 application/pdf Version of Record true Copyright: © 2021 by the authors. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
spellingShingle SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
Sadeer Beden
Qiushi Cao
Arnold Beckmann
title_short SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
title_full SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
title_fullStr SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
title_full_unstemmed SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
title_sort SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0
author_id_str_mv acf0be82092335f6fb65bb51f29c46ac
5c00afca4cb5fa62e43bda660a1a27b5
1439ebd690110a50a797b7ec78cca600
author_id_fullname_str_mv acf0be82092335f6fb65bb51f29c46ac_***_Sadeer Beden
5c00afca4cb5fa62e43bda660a1a27b5_***_Qiushi Cao
1439ebd690110a50a797b7ec78cca600_***_Arnold Beckmann
author Sadeer Beden
Qiushi Cao
Arnold Beckmann
author2 Sadeer Beden
Qiushi Cao
Arnold Beckmann
format Journal article
container_title Information
container_volume 12
container_issue 8
container_start_page 304
publishDate 2021
institution Swansea University
issn 2078-2489
doi_str_mv 10.3390/info12080304
publisher MDPI AG
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description 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.
published_date 2021-07-29T04:13:33Z
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score 11.013731

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