Digital Twins for Software
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2023
Typ der Arbeit
Master
Studiengang
Sammlung
Typ
11 - Studentische Arbeit
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
Patentnummer
Verlag / Herausgebende Institution
Hochschule für Wirtschaft FHNW
Verlagsort / Veranstaltungsort
Olten
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Digital Twins are generally known as representatives of objects of the real world (Bergs et al., 2020, p. 82; Tao et al., 2018, p. 3564). These replica are feeded with the best sensor data, models and other forms of input available to predict the behaviour of its real counterpart (Glaessgen & Stargel, 2012, p. 7). These replicas can be used to better understand such real-life objects. By looking into their behaviour, this might even have reciprocal influence on each other, as they mirror each other (Grieves & Vickers, 2017, p. 93). However, (Parmar et al., 2020, p. 726) state, that with the increasing digitalization of organizations, this will become possible. While (Kerremans, 2017) definition outlines software for an entire organisation, many characteristics of a digital twin can be found within singular software packages, when the software itself is the real asset. The goal of this master thesis is to explore and fill the knowledge-gap with regard to the existing knowledge about Digital Twins of organizations and the missing knowledge about having software itself as the real asset that will be mirrored, a so called Digital Twin for Software. To achieve this goal, the current state of Digital Twins and relevant aspects of software development will be investigated an in-depth interviews will explore, how both aspects can be differentiated. The resulting information is then used to create a framework that helps to guide companies in the application of Digital Twins for Software.
Schlagwörter
Fachgebiet (DDC)
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Begutachtung
Open Access-Status
Lizenz
Zitation
Denz, R. (2023). Digital Twins for Software [Hochschule für Wirtschaft FHNW]. https://irf.fhnw.ch/handle/11654/48686