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Titel: Artificial intelligence in engineering: evolution of virtual product development in the context of medical device industry
VerfasserIn: Schweitzer, Gregor M.
Bitzer, Michael
Vielhaber, Michael
HerausgeberIn: Lutters, Eric
Sprache: Englisch
Titel: Procedia CIRP
Startseite: 349
Endseite: 354
Verlag/Plattform: Elsevier
Erscheinungsjahr: 2021
Erscheinungsort: Amsterdam
Titel der Konferenz: CIRP Design 2021
Konferenzort: Enschede, The Netherlands
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: In this paper a framework is introduced to elicit requirements of Artificial Intelligence (AI) towards the System Model in order to support engineers in Virtual Product Development (VPD). The framework supports to shape the evolution necessary in system modelling to provide the right data in the right quality for AI. Depending on the business benefit that a company wants to realize, AI can provide capabilities and solutions to be implemented in VPD. Therefore, differing requirements need to be fulfilled for each business benefit that a company pursues. This framework is applied in a case study in the Medical Device Industry, where a marked leader wants to improve their capability to create innovations by automatically increasing their market knowledge. Therefore, a Natural Language Processing system is applied to automatically enhance the company knowledge base with an external source. This is realized in an initial prototype by analyzing Tender Documents and automatically connecting the new knowledge generated to the company internal knowledge in the system model. This paper is part of research activities within the Research and Development department of a global Medical Device Company. The Objective of these research activities is to explore the use of Artificial Intelligence to analyze and support the Virtual Development Process.
DOI der Erstveröffentlichung: 10.1016/j.procir.2021.05.081
URL der Erstveröffentlichung: https://www.sciencedirect.com/science/article/pii/S2212827121005485
Link zu diesem Datensatz: hdl:20.500.11880/31499
http://dx.doi.org/10.22028/D291-34335
ISSN: 2212-8271
Datum des Eintrags: 9-Jul-2021
Bemerkung/Hinweis: Procedia CIRP, Volume 100, 2021, Pages 349-354
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Systems Engineering
Professur: NT - Prof. Dr. Michael Vielhaber
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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