Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/43542
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dc.contributor.authorVAN DEN BERGH, Jan-
dc.contributor.authorRodríguez-Echeverría, Jorge-
dc.contributor.authorGautama, Sidharta-
dc.date.accessioned2024-08-02T10:57:56Z-
dc.date.available2024-08-02T10:57:56Z-
dc.date.issued2024-
dc.date.submitted2024-07-24T17:10:16Z-
dc.identifier.citationBramwell-Dicks, Anna; Evans, Abigail; Winckler, Marco; Petrie, Helen; Abdelnour-Nocera, José (Ed.). Design for Equality and Justice INTERACT 2023 IFIP TC 13 Workshops, York, UK, August 28 – September 1, 2023, Revised Selected Papers, Part I, Springer, Cham, p. 20 -30-
dc.identifier.isbn978-3-031-61687-7-
dc.identifier.isbn978-3-031-61688-4-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/1942/43542-
dc.description.abstractThe manufacturing industry is evolving toward more automation and digitization. This includes collecting data from sensors, machines, and software used on the shop floor. Human workers and their strengths and needs are still essential, as recognized by the Industry 5.0 vision. This vision is still abstract, and concepts like human-centricity, digital twin, and production intelligence are still semantically ill-defined to be mapped directly, given the complexity of manufacturing environments. In this paper, we center on the quality management process of Failure Mode and Effects Analysis (FMEA) to propose terminology and a framework to reflect on potential solutions in Industry 5.0. We explore the integration of human and artificial intelligence to create a continuous and actioning quality management process that extends the capabilities of the current process FMEA.-
dc.language.isoen-
dc.publisherSpringer, Cham-
dc.relation.ispartofseriesLecture Notes in Computer Science-
dc.rights2024 IFIP International Federation for Information Processing-
dc.subject.otherIndustry 5.0-
dc.subject.otherInternet of Things-
dc.subject.otherDigital Twin-
dc.subject.otherFMEA-
dc.subject.otherArtificial Intelligence-
dc.titleTowards a Smart Combination of Human and Artificial Intelligence for Manufacturing-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsBramwell-Dicks, Anna-
local.bibliographicCitation.authorsEvans, Abigail-
local.bibliographicCitation.authorsWinckler, Marco-
local.bibliographicCitation.authorsPetrie, Helen-
local.bibliographicCitation.authorsAbdelnour-Nocera, José-
local.bibliographicCitation.conferencedate2023, August 28-September 1-
local.bibliographicCitation.conferencenameInteract 2023-
local.bibliographicCitation.conferenceplaceUniversity of York, York, UK-
dc.identifier.epage30-
dc.identifier.spage20-
dc.identifier.volume14535-
local.bibliographicCitation.jcatC1-
dc.relation.referencesAlbliwi, S., Antony, J., Lim, S.A.H., van der Wiele, T.: Critical failure factors of lean six sigma: a systematic literature review. Int. J. Qual. Reliab. Manag. (2014). https://doi.org/10.1108/IJQRM-09-2013-0147 Article Google Scholar Antony, J., Sony, M.: An empirical study into the limitations and emerging trends of six sigma in manufacturing and service organisations. Int. J. Qual. Reliab. Manag. 37(3), 470–493 (2020) Article Google Scholar Betti, F., de Boer, E.: Global lighthouse network: shaping the next chapter of the fourth industrial revolution (2023) Google Scholar Cambridge dictionary: Asset | English meaning (2023). https://dictionary.cambridge.org/dictionary/english/asset. Accessed 28 May 2023 European Commission, Directorate-General for Research and Innovation, Renda, A., Schwaag Serger, S., Tataj, D., et al.: Industry 5.0, a transformative vision for Europe – Governing systemic transformations towards a sustainable industry. Publications Office of the European Union (2021). https://data.europa.eu/doi/10.2777/17322 AIAG (Automotive Industry Action Group): AIAG & VDA Failure Mode and Effects Analysis - FMEA Handbook, 1st edn. AIAG, 2nd printing Southfild, MI (2022) Google Scholar Hussain, M., et al.: Intelligent knowledge consolidation: from data to wisdom. Knowl.-Based Syst. 234, 107578 (2021). https://doi.org/10.1016/j.knosys.2021.107578, https://www.sciencedirect.com/science/article/pii/S0950705121008406 Leng, J., et al.: Industry 5.0: prospect and retrospect. J. Manuf. Syst. 65, 279–295 (2022). https://doi.org/10.1016/j.jmsy.2022.09.017 Lu, Y., et al.: Outlook on human-centric manufacturing towards industry 5.0. J. Manuf. Syst. 62, 612–627 (2022). https://doi.org/10.1016/j.jmsy.2022.02.001, https://www.sciencedirect.com/science/article/pii/S0278612522000164 Monostori, L.: Cyber-Physical Systems, pp. 1–8. Springer, Berlin, Heidelberg (2018).https://doi.org/10.1007/978-3-642-35950-7_16790-1 Raptis, T.P., Passarella, A., Conti, M.: Data management in industry 4.0: state of the art and open challenges. IEEE Access 7, 97052–97093 (2019) Google Scholar Rowley, J.: The wisdom hierarchy: representations of the DIKW hierarchy. J. Inf. Sci. 33(2), 163–180 (2007). https://doi.org/10.1177/0165551506070706, https://doi.org/10.1177/0165551506070706 Stark, R., Damerau, T.: Digital Twin, pp. 1–8. Springer, Berlin, Heidelberg (2019). https://doi.org/10.1007/978-3-642-35950-7_16870-1 Tao, F., Xiao, B., Qi, Q., Cheng, J., Ji, P.: Digital twin modeling. J. Manuf. Syst. 64, 372–389 (2022). https://doi.org/10.1016/j.jmsy.2022.06.015, https://www.sciencedirect.com/science/article/pii/S0278612522001108 Wang, D.: Building value in a world of technological change: data analytics and industry 4.0. IEEE Eng. Manag. Rev. 46(1), 32–33 (2018). https://doi.org/10.1109/EMR.2018.2809915-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr14535-
dc.identifier.doi10.1007/978-3-031-61688-4_3-
dc.identifier.isi001290150900003-
dc.identifier.eissn1611-3349-
local.provider.typePdf-
local.bibliographicCitation.btitleDesign for Equality and Justice INTERACT 2023 IFIP TC 13 Workshops, York, UK, August 28 – September 1, 2023, Revised Selected Papers, Part I-
local.uhasselt.internationalyes-
item.contributorVAN DEN BERGH, Jan-
item.contributorRodríguez-Echeverría, Jorge-
item.contributorGautama, Sidharta-
item.fulltextWith Fulltext-
item.fullcitationVAN DEN BERGH, Jan; Rodríguez-Echeverría, Jorge & Gautama, Sidharta (2024) Towards a Smart Combination of Human and Artificial Intelligence for Manufacturing. In: Bramwell-Dicks, Anna; Evans, Abigail; Winckler, Marco; Petrie, Helen; Abdelnour-Nocera, José (Ed.). Design for Equality and Justice INTERACT 2023 IFIP TC 13 Workshops, York, UK, August 28 – September 1, 2023, Revised Selected Papers, Part I, Springer, Cham, p. 20 -30.-
item.accessRightsOpen Access-
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