Ontology-based augmented reality content-related techniques and their impact in knowledge capture and re-use within maintenance diagnosis

dc.contributor.advisorErkoyuncu, John Ahmet
dc.contributor.authorFernandez Del Amo Blanco, Inigo
dc.date.accessioned2023-09-28T10:37:00Z
dc.date.available2023-09-28T10:37:00Z
dc.date.issued2020-05
dc.description.abstractThis PhD thesis aims to study ontology-based AR content-related methods and their impact in knowledge transfer, capture and re-use for cost-effective human knowledge integration in digital diagnostic systems. Industry 4.0 has revealed the importance of maintainers’ knowledge capture and re-use in diagnostics systems for providing satisfactory solutions in cases where those systems cannot (e.g. nofault-found). Augmented Reality (AR) utilises content-related techniques to transfer knowledge to maintainers for improving efficiency and effectiveness of diagnosis tasks. Academic literature has shown that AR can also be utilised for knowledge capture and re-use, but this has only been demonstrated in simple, step-by-step repair operations. In diagnosis research, ontology-based methods are applied to capture and re-use knowledge from unstructured and heterogenous sources like humans. Nevertheless, these methods have not made use of AR potential to contextualise knowledge and so, improve efficiency and effectiveness of knowledge capture and re-use diagnosis operations...[cont.]en_UK
dc.description.coursenameManufacturingen_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20292
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.publisher.departmentSATMen_UK
dc.rights© Cranfield University, 2020. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.en_UK
dc.titleOntology-based augmented reality content-related techniques and their impact in knowledge capture and re-use within maintenance diagnosisen_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelDoctoralen_UK
dc.type.qualificationnamePhDen_UK

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