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Titel: A review of digital assistants in production and logistics: applications, benefits, and challenges
VerfasserIn: Zheng, Ting
Grosse, Eric H.
Morana, Stefan
Glock, Christoph H.
Sprache: Englisch
Titel: International journal of production research
Bandnummer: 62
Heft: 21
Seiten: 8022-8048
Verlag/Plattform: Taylor & Francis
Erscheinungsjahr: 2024
Freie Schlagwörter: Digital assistant
Artificial intelligence
Production
Logistics
Systematic literature review
Industry 5.0
DDC-Sachgruppe: 330 Wirtschaft
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: This study presents a systematic literature review to understand the applications, benefits, and challenges of digital assistants (DAs) in production and logistics tasks. Our conceptual framework covers three dimensions: information management, collaborative operations, and knowledge transfer. We evaluate human-DA collaborative tasks in the areas of product design, production, maintenance, quality management, and logistics. This allows us to expand upon different types of DAs, and reveal how they improve the speed and ease of production and logistic work, which was ignored in previous studies. Our results demonstrate that DAs improve the speed and ease of workers’ interaction with machines/information systems in searching, processing, and demonstrating. Extant studies describe DAs with different levels of autonomy in decision-making; however, most DAs perform tasks as instructed or with workers’ consent. Additionally, we observe that workers find it more intuitive to perform tasks and acquire knowledge when they receive multiple sensorial cues (e.g. auditory and visual cues). Consequently, future research can explore how DAs can be integrated with other technologies for robust multi-modal assistance such as eye tracking and augmented reality. This can provide customised DA support to workers with disabilities or conditions to facilitate more inclusive production and logistics.
DOI der Erstveröffentlichung: 10.1080/00207543.2024.2330631
URL der Erstveröffentlichung: https://www.tandfonline.com/doi/full/10.1080/00207543.2024.2330631
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-433748
hdl:20.500.11880/38901
http://dx.doi.org/10.22028/D291-43374
ISSN: 1366-588X
0020-7543
Datum des Eintrags: 6-Nov-2024
Fakultät: HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
Fachrichtung: HW - Wirtschaftswissenschaft
Professur: HW - Prof. Dr. Stefan Morana
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons Creative Commons