A systematic literature review of process mining in industrial and manufacturing environments (Master thesis)

Κυριακίδης, Θεόδωρος/ Kyriakidis, Theodoros/ Oil and Gas Technology

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dc.contributor.authorΚυριακίδης, Θεόδωροςel
dc.contributor.authorKyriakidis, Theodorosen
dc.date.accessioned2026-07-10T10:11:52Z-
dc.date.available2026-07-10T10:11:52Z-
dc.identifier.urihttps://repo.lib.duth.gr/jspui/handle/123456789/22648-
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectΕξόρυξη διαδικασιώνel
dc.subjectΒιβλιομετρίαel
dc.subjectΤεχνητή νοημοσύνηel
dc.subjectΒιομηχανικά περιβάλλονταel
dc.subjectΨηφιακό δίδυμοel
dc.subjectProcess miningen
dc.subjectBibliometricsen
dc.subjectArtificial intelligenceen
dc.subjectIndustrial environmentsen
dc.subjectDigital twinen
dc.titleA systematic literature review of process mining in industrial and manufacturing environmentsen
heal.typemasterThesis-
heal.generalDescriptionΒιβλιογραφία: σ. 55-61el
heal.generalDescriptionΠρόγραμμα Μεταπτυχιακών Σπουδών «Τεχνολογία Πετρελαίου και Φυσικού Αερίου (Oil and Gas Technology)»el
heal.classificationProcess miningen
heal.dateAvailable2026-07-10T10:12:52Z-
heal.languageen-
heal.accessfree-
heal.recordProviderΔημοκρίτειο Πανεπιστήμιο Θράκης. Σχολή θετικών επιστημών. Τμήμα Χημείαςel
heal.publicationDate2025-01-28-
heal.abstractThe thesis aims to systematically record existing works on the intersection of manufacturing with process mining and investigate the recorded scientific knowledge through a bibliometric approach. To achieve this specific goal, 163 studies from the Web of Science were analyzed and contained the query: ("process mining" or "event log" or "conformance checking" or "process discovery") and (industry* or manufacturing * or industrial*) in the titles, in the abstract, in the keyword plus and in the author keywords. To be able to implement this analysis, it was done with the help of R studio with the bibliometrix package, which uses R as a programming language. The analysis covered the timeframe from 2012 to 2023. The analyses that have been conducted make it clear that there is a rapid increase in the use of process mining in industrial environments. This trend is significant as it indicates the growing importance of digital technologies in industry, particularly in developing the digital twin and artificial intelligence. Keywords such as process mining, artificial intelligence and digital twin are the most widespread. An analysis is also conducted for the critical bibliometric trends and the influential trends of process mining in industrial and manufacturing environments, as well as the shaping of the research landscape in terms of its conceptual structure, intellectual structure, and social structure. Finally, performance analysis was conducted based on the bibliometric analysis resultsen
heal.advisorNameΔελιάς, Παύλοςel
heal.committeeMemberNameΔελιάς, Παύλοςel
heal.committeeMemberNameΚόκκινος, Νικόλαοςel
heal.committeeMemberNameΜήττας, Νικόλαοςel
heal.committeeMemberNameDelias, Pavlosen
heal.committeeMemberNameKokkinos, Nikolaosen
heal.committeeMemberNameMittas, Nikolaosen
heal.academicPublisherΤμήμα Χημείαςel
heal.academicPublisherIDduth-
heal.numberOfPages71 σ.-
heal.fullTextAvailabilitytrue-
heal.type.enMaster thesisen
heal.type.elΜεταπτυχιακή εργασίαel
dc.contributor.masterOil and Gas Technologyen
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https://repo.lib.duth.gr/jspui/handle/123456789/22648
http://dx.doi.org/10.26257/heal.duth.21322
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