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  4. Photometric Stereo for Tool Wear Monitoring: Addressing Challenges of Specular Surfaces in Sheet Metal Forming
 
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2025
Journal Article
Title

Photometric Stereo for Tool Wear Monitoring: Addressing Challenges of Specular Surfaces in Sheet Metal Forming

Abstract
The progressive forming of sheet metal through stages such as blanking, deep-drawing and ironing is an economically attractive route to complex components. Wear control is decisive for product quality, as it prevents defects and minimizes scrap. Optical sensors are increasingly supplementing conventional monitoring, thanks to ongoing digitization and continuous improvement of availability. This paper introduces a modular, adaptive, camera-based measurement stage that captures component geometry and delivers cause-specific feedback on tool wear, enabling anomalies to be linked to individual forming steps. The system employs photometric stereo analysis: several images are taken under different illumination angles. A normal map is reconstructed, and pixel-wise brightness differences reveal the surface topology. Deviations from target geometry are then localized by comparing actual and nominal data. A key contribution of the present work is the systematic investigation of highly reflective workpiece materials-in contrast to previous studies based on CR DC04 steel, whose matte finish approximates Lambertian behavior. Specular surfaces, such as the ETSR TS245, distort the incident light field, violating this assumption and reducing detection accuracy. Therefore, it is necessary to analyze how variations in reflectivity and surface finishes influence the photometric stereo pipeline. In addition, calibration and illumination strategies are proposed that restore reliable anomaly detection even for glossy substrates. This study lays the groundwork for efficient, robust and adaptive manufacturing systems by providing process insights without disrupting production and addressing the challenges posed by non-Lambertian reflections. It advances intelligent forming technology across varying materials in manufacturing processes.
Author(s)
Moske, Jonas
TU Darmstadt, Institut für Produktionstechnik und Umformmaschinen  
Kutlu, Hasan  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Groenewold, Phil
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Santos, Pedro
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Weinmann, Andreas
Hochschule Darmstadt  
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Groche, Peter
TU Darmstadt, Institut für Produktionstechnik und Umformmaschinen  
Journal
Manufacturing Review. Online journal  
Project(s)
Aufbau einer Methode zur Erkennung von Verschleißzuständen in mehrstufigen Blechumformprozessen anhand In-situ aufgezeichneter Prozessgröße
Aufbau einer Methode zur Erkennung von Verschleißzuständen in mehrstufigen Blechumformprozessen anhand In-situ aufgezeichneter Prozessgröße
Funder
Bundesministerium für Wirtschaft und Energie  
Deutsches Zentrum für Luft- und Raumfahrt  
Open Access
File(s)
Download (8.29 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1051/mfreview/2025026
10.24406/publica-7164
Additional link
Full text
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Manufacturing and Mobility

  • Research Line: Computer vision (CV)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • 3D Scanning

  • Photometry

  • Industrial quality control

  • Quality assurance

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