; ; ; ; ;
In
17th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME ‘23) / edited by Roberto Teti (Prof.)
In
Procedia CIRP 126, Seiten/Artikel-Nr.:498-503
2024
Online
DOI: 10.1016/j.procir.2024.08.408
DOI: 10.18154/RWTH-2025-02092
URL: https://publications.rwth-aachen.de/record/1005907/files/1005907.pdf
Einrichtungen
Projekte
Inhaltliche Beschreibung (Schlagwörter)
ECDMTF100 (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-s2.0-85208581724
Interne Identnummern
RWTH-2025-02092
Datensatz-ID: 1005907
Beteiligte Länder
Germany
Journal Article/Contribution to a book/Contribution to a conference proceedings
Evaluation of process stability in precise electrochemical machining using machine learning models based on extracted features
17. CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2023, IschiaIschia, Italy, 12 Jul 2023 - 14 Jul 2023
Procedia CIRP 126, 498-503 (2024) special issue: "17th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME ‘23) / edited by Roberto Teti (Prof.)" (9798331306984)
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