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KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0

Qiushi Cao, Cecilia Zanni-Merk, Ahmed Samet, Christoph Reich, François de Bertrand de Beuvron, Arnold Beckmann Orcid Logo, Cinzia Giannetti Orcid Logo

Robotics and Computer-Integrated Manufacturing, Volume: 74, Start page: 102281

Swansea University Authors: Qiushi Cao , Arnold Beckmann Orcid Logo, Cinzia Giannetti Orcid Logo

  • Accepted Manuscript under embargo until: 12th November 2022
Published in: Robotics and Computer-Integrated Manufacturing
ISSN: 0736-5845
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58508
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first_indexed 2021-10-28T15:19:52Z
last_indexed 2021-11-24T04:15:59Z
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spelling 2021-11-23T10:20:14.1770462 v2 58508 2021-10-28 KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0 5c00afca4cb5fa62e43bda660a1a27b5 Qiushi Cao Qiushi Cao true false 1439ebd690110a50a797b7ec78cca600 0000-0001-7958-5790 Arnold Beckmann Arnold Beckmann true false a8d947a38cb58a8d2dfe6f50cb7eb1c6 0000-0003-0339-5872 Cinzia Giannetti Cinzia Giannetti true false 2021-10-28 MTLS Journal Article Robotics and Computer-Integrated Manufacturing 74 102281 Elsevier BV 0736-5845 Industry 4.0; Predictive maintenance; Knowledge-based system; Chronicle mining; Ontology reasoning 1 4 2022 2022-04-01 10.1016/j.rcim.2021.102281 COLLEGE NANME Materials Science and Engineering COLLEGE CODE MTLS Swansea University INTERREG Upper Rhine (European Regional Development Fund), Engineering and Physical Sciences Research Council (EPSRC) EP/S018107/1, EP/S001387/1 2021-11-23T10:20:14.1770462 2021-10-28T16:10:27.1366034 College of Science Computer Science Qiushi Cao 1 Cecilia Zanni-Merk 2 Ahmed Samet 3 Christoph Reich 4 François de Bertrand de Beuvron 5 Arnold Beckmann 0000-0001-7958-5790 6 Cinzia Giannetti 0000-0003-0339-5872 7 Under embargo Under embargo 2021-10-28T16:21:00.3152565 Output 7206137 application/pdf Accepted Manuscript true 2022-11-12T00:00:00.0000000 ©2021 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng https://creativecommons.org/licenses/by-nc-nd/4.0/
title KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
spellingShingle KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
Qiushi, Cao
Arnold, Beckmann
Cinzia, Giannetti
title_short KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
title_full KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
title_fullStr KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
title_full_unstemmed KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
title_sort KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0
author_id_str_mv 5c00afca4cb5fa62e43bda660a1a27b5
1439ebd690110a50a797b7ec78cca600
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author_id_fullname_str_mv 5c00afca4cb5fa62e43bda660a1a27b5_***_Qiushi, Cao_***_
1439ebd690110a50a797b7ec78cca600_***_Arnold, Beckmann_***_0000-0001-7958-5790
a8d947a38cb58a8d2dfe6f50cb7eb1c6_***_Cinzia, Giannetti_***_0000-0003-0339-5872
author Qiushi, Cao
Arnold, Beckmann
Cinzia, Giannetti
author2 Qiushi Cao
Cecilia Zanni-Merk
Ahmed Samet
Christoph Reich
François de Bertrand de Beuvron
Arnold Beckmann
Cinzia Giannetti
format Journal article
container_title Robotics and Computer-Integrated Manufacturing
container_volume 74
container_start_page 102281
publishDate 2022
institution Swansea University
issn 0736-5845
doi_str_mv 10.1016/j.rcim.2021.102281
publisher Elsevier BV
college_str College of Science
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hierarchy_top_id collegeofscience
hierarchy_top_title College of Science
hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
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published_date 2022-04-01T04:28:42Z
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