Details
| Titel in Übersetzung | Applications of machine learning in manufacturing from a job order and product perspective an overview |
|---|---|
| Originalsprache | Deutsch |
| Seiten (von - bis) | 358-362 |
| Seitenumfang | 5 |
| Fachzeitschrift | ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb |
| Jahrgang | 116 |
| Ausgabenummer | 5 |
| Frühes Online-Datum | 19 Mai 2021 |
| Publikationsstatus | Veröffentlicht - 31 Mai 2021 |
Abstract
Machine learning as a subfield of artificial intelligence can contribute to accelerating the design of processes in manufacturing, reducing cycle times, improving quality, and making better use of production capacities. This article provides a systematized overview of machine learning applications for product- and order-related processes and supports practitioners in identifying application areas in a focused manner and exploiting value-added potential.
Schlagwörter
- Machine learning, Order-related processes, Product-related processes, Production control, Production planning, Use cases
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Strategie und Management
- Entscheidungswissenschaften (insg.)
- Managementlehre und Operations Resarch
Zitieren
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- BibTex
- RIS
in: ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, Jahrgang 116, Nr. 5, 31.05.2021, S. 358-362.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung
}
TY - JOUR
T1 - Anwendungen des maschinellen Lernens in der Produktion aus Auftrags- und Produktsicht
T2 - Ein Überblick
AU - Denkena, Berend
AU - Dittrich, Marc André
AU - Noske, Hendrik
AU - Kramer, Kathrin
AU - Schmidt, Matthias
PY - 2021/5/31
Y1 - 2021/5/31
N2 - Machine learning as a subfield of artificial intelligence can contribute to accelerating the design of processes in manufacturing, reducing cycle times, improving quality, and making better use of production capacities. This article provides a systematized overview of machine learning applications for product- and order-related processes and supports practitioners in identifying application areas in a focused manner and exploiting value-added potential.
AB - Machine learning as a subfield of artificial intelligence can contribute to accelerating the design of processes in manufacturing, reducing cycle times, improving quality, and making better use of production capacities. This article provides a systematized overview of machine learning applications for product- and order-related processes and supports practitioners in identifying application areas in a focused manner and exploiting value-added potential.
KW - Machine learning
KW - Order-related processes
KW - Product-related processes
KW - Production control
KW - Production planning
KW - Use cases
UR - http://www.scopus.com/inward/record.url?scp=85106971450&partnerID=8YFLogxK
U2 - 10.1515/zwf-2021-0068
DO - 10.1515/zwf-2021-0068
M3 - Artikel
AN - SCOPUS:85106971450
VL - 116
SP - 358
EP - 362
JO - ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
JF - ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
SN - 0947-0085
IS - 5
ER -