Material-dependent predictive modeling of component quality in a backward extrusion process from coil

Harms A, Krüger M, Höfgen J, Hujo-Lauer D, Vogel-Heuser B, Merklein M (2026)

Publication Language: English

Publication Type: Journal article

Publication year: 2026

Journal

Production Engineering Wissenschaftliche Gesellschaft für Produktionstechnik (WGP)

Book Volume: 20

Article Number: 57

Issue: 2

DOI: 10.1007/s11740-026-01433-7

Abstract

The increasing demand for lightweight components with enhanced functional integration is pushing established manufacturing technologies to their limits. In continuous sheet-bulk metal forming, tool life and process stability can directly affect component quality, while robust prediction methods for quality characteristics and tool loading are still limited. This study investigates backward extrusion from coil and quantifies the correlation between punch displacement and two quality relevant responses, namely the residual sheet thickness and the peak punch force. Experiments were performed on a 30 mm wide steel strip with an initial thickness of 2 mm using two materials, the deep drawing steel DC04 and the high strength steel S500MC. More than 100,000 strokes were evaluated. Material behavior was characterized by miniaturized upsetting tests, providing the initial yield stress and the strain hardening exponent. The experimental results reveal an approximately linear relationship between tool position and residual thickness, as well as between tool position and peak force, for both steels under steady state conditions. DC04 exhibits a stronger response to tool position than S500MC, consistent with its higher strain hardening. Based on these findings, semi analytical expressions are derived that link the linear model parameters to the initial yield stress and strain hardening exponent. The resulting material dependent model predicts residual thickness and punch force within the investigated range with high accuracy and offers a computationally efficient alternative to numerical simulation for rapid process design, assessment of material effects, and future online monitoring of backward extrusion from coil.

Authors with CRIS profile

Arnold Harms Institute of Manufacturing Technology (LFT) Marion Merklein Institute of Manufacturing Technology (LFT)

Related research project(s)

Data-based identification and prediction of the die surface condition and interactions in sheet bulk metal forming processes from coil SPP 2422: Datengetriebene Prozessmodellierung in der Umformtechnik Nov. 1, 2023 - Oct. 31, 2026

Involved external institutions

Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Harms, A., Krüger, M., Höfgen, J., Hujo-Lauer, D., Vogel-Heuser, B., & Merklein, M. (2026). Material-dependent predictive modeling of component quality in a backward extrusion process from coil. Production Engineering, 20. https://doi.org/10.1007/s11740-026-01433-7

MLA:

Harms, Arnold, et al. "Material-dependent predictive modeling of component quality in a backward extrusion process from coil." Production Engineering 20 (2026).

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