Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

External Research Organisations

  • German National Library of Science and Technology (TIB)
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Details

Original languageEnglish
Title of host publicationAdvances in System-Integrated Intelligence
Subtitle of host publicationProceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy
EditorsMaurizio Valle, Dirk Lehmhus, Christian Gianoglio, Edoardo Ragusa, Lucia Seminara, Stefan Bosse, Ali Ibrahim, Klaus-Dieter Thoben
Place of PublicationCham
PublisherSpringer Science and Business Media Deutschland GmbH
Pages415-424
Number of pages10
ISBN (electronic)978-3-031-16281-7
ISBN (print)9783031162800
Publication statusPublished - 4 Sept 2022
Event6th International Conference on System-Integrated Intelligence, SysInt 2022 - Genova, Italy
Duration: 7 Sept 20229 Sept 2022

Publication series

NameLecture Notes in Networks and Systems
Volume546 LNNS
ISSN (Print)2367-3370
ISSN (electronic)2367-3389

Abstract

The development of a novel manufacturing process chain is a complex scientific challenge and requires interdisciplinary and inter-institutional collaboration. Data need to be exchanged continuously between involved researchers in order to coordinate between individual process steps and to identify cause-effect relationships within the process. This publication describes an approach to provide seamless digital access to quality-related data and to further structure, semantically annotate and link process- and quality-relevant data. It uses a domain-specific ontology called Visual Inspection Ontology embedded in a Knowledge Management System to support the documentation of a quality-determining process. The ontology is applied to a use case from the development of a novel process chain to manufacture multi-material shafts within the Collaborative Research Centre (CRC) 1153. A workflow to establish quality control measures regarding a novel process chain for multi-material high-performance components under development based on the proposed ontology is presented.

Keywords

    Human machine interaction, Knowledge management system, Sample monitoring, Semantic annotation, Tailored Forming

ASJC Scopus subject areas

Cite this

Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection. / Sheveleva, Tatyana; Herrmann, Kevin; Wawer, Max Leo et al.
Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy. ed. / Maurizio Valle; Dirk Lehmhus; Christian Gianoglio; Edoardo Ragusa; Lucia Seminara; Stefan Bosse; Ali Ibrahim; Klaus-Dieter Thoben. Cham: Springer Science and Business Media Deutschland GmbH, 2022. p. 415-424 (Lecture Notes in Networks and Systems; Vol. 546 LNNS).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Sheveleva, T, Herrmann, K, Wawer, ML, Kahra, C, Nürnberger, F, Koepler, O, Mozgova, I, Lachmayer, R & Auer, S 2022, Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection. in M Valle, D Lehmhus, C Gianoglio, E Ragusa, L Seminara, S Bosse, A Ibrahim & K-D Thoben (eds), Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy. Lecture Notes in Networks and Systems, vol. 546 LNNS, Springer Science and Business Media Deutschland GmbH, Cham, pp. 415-424, 6th International Conference on System-Integrated Intelligence, SysInt 2022, Genova, Italy, 7 Sept 2022. https://doi.org/10.15488/13181, https://doi.org/10.1007/978-3-031-16281-7_39
Sheveleva, T., Herrmann, K., Wawer, M. L., Kahra, C., Nürnberger, F., Koepler, O., Mozgova, I., Lachmayer, R., & Auer, S. (2022). Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection. In M. Valle, D. Lehmhus, C. Gianoglio, E. Ragusa, L. Seminara, S. Bosse, A. Ibrahim, & K.-D. Thoben (Eds.), Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy (pp. 415-424). (Lecture Notes in Networks and Systems; Vol. 546 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.15488/13181, https://doi.org/10.1007/978-3-031-16281-7_39
Sheveleva T, Herrmann K, Wawer ML, Kahra C, Nürnberger F, Koepler O et al. Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection. In Valle M, Lehmhus D, Gianoglio C, Ragusa E, Seminara L, Bosse S, Ibrahim A, Thoben KD, editors, Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy. Cham: Springer Science and Business Media Deutschland GmbH. 2022. p. 415-424. (Lecture Notes in Networks and Systems). doi: 10.15488/13181, 10.1007/978-3-031-16281-7_39
Sheveleva, Tatyana ; Herrmann, Kevin ; Wawer, Max Leo et al. / Ontology-Based Documentation of Quality Assurance Measures Using the Example of a Visual Inspection. Advances in System-Integrated Intelligence: Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy. editor / Maurizio Valle ; Dirk Lehmhus ; Christian Gianoglio ; Edoardo Ragusa ; Lucia Seminara ; Stefan Bosse ; Ali Ibrahim ; Klaus-Dieter Thoben. Cham : Springer Science and Business Media Deutschland GmbH, 2022. pp. 415-424 (Lecture Notes in Networks and Systems).
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abstract = "The development of a novel manufacturing process chain is a complex scientific challenge and requires interdisciplinary and inter-institutional collaboration. Data need to be exchanged continuously between involved researchers in order to coordinate between individual process steps and to identify cause-effect relationships within the process. This publication describes an approach to provide seamless digital access to quality-related data and to further structure, semantically annotate and link process- and quality-relevant data. It uses a domain-specific ontology called Visual Inspection Ontology embedded in a Knowledge Management System to support the documentation of a quality-determining process. The ontology is applied to a use case from the development of a novel process chain to manufacture multi-material shafts within the Collaborative Research Centre (CRC) 1153. A workflow to establish quality control measures regarding a novel process chain for multi-material high-performance components under development based on the proposed ontology is presented.",
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