guest ::
Application of time series data mining for the prediction of transition times in production
; ; ;
In
53rd CIRP Conference on Manufacturing Systems 2020 : 53rd CIRP Conference on Manufacturing Systems / Edited by Robert X. Gao, Kornel Ehmann
In
Procedia CIRP 93, Seiten/Artikel-Nr.:897-902
2020
Konferenzort: Chicago, USA
Online
DOI: 10.1016/j.procir.2020.04.054
DOI: 10.18154/RWTH-2021-06587
URL: https://publications.rwth-aachen.de/record/822188/files/822188.pdf
Einrichtungen
Inhaltliche Beschreibung (Schlagwörter)
Automatisierung (frei) ; Komplexität (frei) ; Logistik (frei) ; Maschinenbau (frei) ; Modellierung (frei) ; Optimierung (frei) ; Production Process (frei) ; Produktion (frei) ; Prozessoptimierung (frei)
Thematische Einordnung (Klassifikation)
DDC: 670
OpenAccess: 
PDF
Dokumenttyp
Journal Article/Contribution to a conference proceedings
Format
online
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85092433897
Interne Identnummern
RWTH-2021-06587
Datensatz-ID: 822188
Beteiligte Länder
Germany
Related:
Journal Article/Contribution to a conference proceedings/Contribution to a book
Application of time series data mining for the prediction of transition times in production
53. CIRP Conference on Manufacturing Systems, CIRP CMS 2020, onlineonline, 1 Jul 2020 - 3 Jul 2020
Procedia CIRP 93, 897-902 (2020) special issue: "53rd CIRP Conference on Manufacturing Systems 2020 : 53rd CIRP Conference on Manufacturing Systems / Edited by Robert X. Gao, Kornel Ehmann" (9781713818809)
BibTeX |
EndNote:
XML,
Text |
RIS
; 
; 
; SCOPUS
PDF