KI-gestützte Prozessoptimierung in der Massivumformung

Claudia Glaubitz; Julian Raible; Helena Monke; Marcel Rothgänger; Julius Peddinghaus; Kai Brunotte

doi:10.1515/zwf-2024-0124

KI-gestützte Prozessoptimierung in der Massivumformung

Claudia Glaubitz^*, Julian Raible, Helena Monke, Marcel Rothgänger, Julius Peddinghaus, Kai Brunotte

^*Korrespondierende*r Autor*in für diese Arbeit

Institut für Umformtechnik und Umformmaschinen

Universität Stuttgart

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Abstract

AI-Supported Process Optimization in Bulk Metal Forming. The subproject “Transparent AI-Based Process Modelling in Die Forging” of the Priority Program (SPP) 2422 of the German Research Foundation (DFG) aims to optimize die forging through the use of artificial intelligence (AI). Currently, material allowances are used to compensate for process fluctuations. Explainable AI models enable the analysis of the interactions between process parameters and geometric deviations and are intended to be used in the future to optimize process and tool design. This can reduce material and energy requirements, contributing increasing sustainability in bulk metal forming.

Titel in Übersetzung	AI-supported process optimization in bulk metal forming
Originalsprache	Deutsch
Seiten (von - bis)	257-262
Seitenumfang	6
Fachzeitschrift	ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
Jahrgang	120
Ausgabenummer	s1
DOIs	https://doi.org/10.1515/zwf-2024-0124
Publikationsstatus	Veröffentlicht - 20 März 2025

Schlagwörter

Artificial Intelligence (AI)
Die Forging
In-line Optimization Potential
Parameter Correlation

ASJC Scopus Sachgebiete

Allgemeiner Maschinenbau
Strategie und Management
Managementlehre und Operations Resarch

Zugriff auf Dokument

10.1515/zwf-2024-0124Lizenz: CC BY 4.0

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

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AU - Brunotte, Kai

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