Contributions to increasing the accuracy and reducing the forming forces of robot-based two-point incremental forming

This article presents the latest research results on the enhancement of robot-based incremental sheet metal forming performance in detail and comprehensively. Since the low robot stiffness leads to deformations of the robot and thus deviations of the final part, the presented contributions aim for increasing the part accuracy. The article demonstrates how an advanced sensor network, analogous to a µGPS, can be established for tracking the tool pose utilizing innovative shadow imaging sensor technology. Static experiments show that a measurement uncertainty below of 50 µm is achievable after the correction of systematic errors. Additional experiments demonstrated the applicability of the sensor network for measuring the tool position on a moving robot. Based on the measurement, a robot position correction will be enabled to achieve a reduction of machine-dependent component tolerances. A further approach to reduce the geometric deviations due to robot deformation is reducing the forming forces in robot-based two-point incremental forming. This is achieved by a modular vibration unit that has been specially developed for this purpose. The introduction of ultrasonic vibrations into the forming process has been shown to reduce the forces in the sheet metal plane by 70%. As a result, the sensor network and the introduction of ultrasonic vibrations provide a robust foundation for the advancement of higher accuracy classes with cost-effective robot technology, which is becoming increasingly crucial in the industry.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-05-07
DOI
https://doi.org/10.1051/matecconf/202540801057/pdf
Primary Topic
Metal Forming Simulation Techniques
Type
article
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article

Contributions to increasing the accuracy and reducing the forming forces of robot-based two-point incremental forming

Springer Link (Chiba Institute of Technology)
Metal Forming Simulation Techniques
article

Contributions to increasing the accuracy and reducing the forming forces of robot-based two-point incremental forming

article en

Abstract

This article presents the latest research results on the enhancement of robot-based incremental sheet metal forming performance in detail and comprehensively. Since the low robot stiffness leads to deformations of the robot and thus deviations of the final part, the presented contributions aim for increasing the part accuracy. The article demonstrates how an advanced sensor network, analogous to a µGPS, can be established for tracking the tool pose utilizing innovative shadow imaging sensor technology. Static experiments show that a measurement uncertainty below of 50 µm is achievable after the correction of systematic errors. Additional experiments demonstrated the applicability of the sensor network for measuring the tool position on a moving robot. Based on the measurement, a robot position correction will be enabled to achieve a reduction of machine-dependent component tolerances. A further approach to reduce the geometric deviations due to robot deformation is reducing the forming forces in robot-based two-point incremental forming. This is achieved by a modular vibration unit that has been specially developed for this purpose. The introduction of ultrasonic vibrations into the forming process has been shown to reduce the forces in the sheet metal plane by 70%. As a result, the sensor network and the introduction of ultrasonic vibrations provide a robust foundation for the advancement of higher accuracy classes with cost-effective robot technology, which is becoming increasingly crucial in the industry.

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 55%
Metal Forming Simulation Techniques
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Contributions to increasing the accuracy and reducing the forming forces of robot-based two-point incremental forming · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS