Optical Quality Control for Adaptive Polishing Processes

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Marc Kassubeck
  • Talash Malek
  • Moritz Muhlhausen
  • Moritz Kappel
  • Susana Castillo
  • Marc Andre Dittrich
  • Marcus Magnor

Externe Organisationen

  • Technische Universität Braunschweig
  • University of New Mexico
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten90-94
Seitenumfang5
ISBN (elektronisch)9781728157450
ISBN (Print)978-1-7281-5744-3, 978-1-7281-5746-7
PublikationsstatusVeröffentlicht - 2020
Veranstaltung2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Santa Fe, USA / Vereinigte Staaten
Dauer: 29 März 202031 März 2020

Publikationsreihe

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
Band2020-March

Abstract

We propose an image-based method to automatically estimate the surface roughness of a polishing process carried out by a numerically controlled machine tool. Given a single photograph of the workpiece, we incorporate techniques from differentiable rendering to infer the object's roughness parameters, resulting in several advantages over existing approaches: since the method fully accounts for global light transport effects, the estimation can occur under general, known lighting conditions and workpiece geometries. This allows deployment of our approach for in-situ measurements by simply equipping the machine tool with a standard digital camera capturing photos of the workpiece. We investigate the feasibility and effectiveness of our novel method in a prototype application considering polished brass plates. Our results demonstrate a promising direction for surface parameter measurement in less restricted polishing process environments.

ASJC Scopus Sachgebiete

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Optical Quality Control for Adaptive Polishing Processes. / Kassubeck, Marc; Malek, Talash; Muhlhausen, Moritz et al.
2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. S. 90-94 9094615 (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation; Band 2020-March).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kassubeck, M, Malek, T, Muhlhausen, M, Kappel, M, Castillo, S, Dittrich, MA & Magnor, M 2020, Optical Quality Control for Adaptive Polishing Processes. in 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings., 9094615, Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, Bd. 2020-March, Institute of Electrical and Electronics Engineers Inc., S. 90-94, 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020, Santa Fe, USA / Vereinigte Staaten, 29 März 2020. https://doi.org/10.1109/ssiai49293.2020.9094615
Kassubeck, M., Malek, T., Muhlhausen, M., Kappel, M., Castillo, S., Dittrich, M. A., & Magnor, M. (2020). Optical Quality Control for Adaptive Polishing Processes. In 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings (S. 90-94). Artikel 9094615 (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation; Band 2020-March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ssiai49293.2020.9094615
Kassubeck M, Malek T, Muhlhausen M, Kappel M, Castillo S, Dittrich MA et al. Optical Quality Control for Adaptive Polishing Processes. in 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. S. 90-94. 9094615. (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation). doi: 10.1109/ssiai49293.2020.9094615
Kassubeck, Marc ; Malek, Talash ; Muhlhausen, Moritz et al. / Optical Quality Control for Adaptive Polishing Processes. 2020 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. S. 90-94 (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation).
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title = "Optical Quality Control for Adaptive Polishing Processes",
abstract = "We propose an image-based method to automatically estimate the surface roughness of a polishing process carried out by a numerically controlled machine tool. Given a single photograph of the workpiece, we incorporate techniques from differentiable rendering to infer the object's roughness parameters, resulting in several advantages over existing approaches: since the method fully accounts for global light transport effects, the estimation can occur under general, known lighting conditions and workpiece geometries. This allows deployment of our approach for in-situ measurements by simply equipping the machine tool with a standard digital camera capturing photos of the workpiece. We investigate the feasibility and effectiveness of our novel method in a prototype application considering polished brass plates. Our results demonstrate a promising direction for surface parameter measurement in less restricted polishing process environments.",
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AU - Kassubeck, Marc

AU - Malek, Talash

AU - Muhlhausen, Moritz

AU - Kappel, Moritz

AU - Castillo, Susana

AU - Dittrich, Marc Andre

AU - Magnor, Marcus

N1 - Funding Information: This research has been funded by the Deutsche Forschungsge-meinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the Cluster of Excellence PhoenixD (EXC 2122, Project ID 390833453).

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AB - We propose an image-based method to automatically estimate the surface roughness of a polishing process carried out by a numerically controlled machine tool. Given a single photograph of the workpiece, we incorporate techniques from differentiable rendering to infer the object's roughness parameters, resulting in several advantages over existing approaches: since the method fully accounts for global light transport effects, the estimation can occur under general, known lighting conditions and workpiece geometries. This allows deployment of our approach for in-situ measurements by simply equipping the machine tool with a standard digital camera capturing photos of the workpiece. We investigate the feasibility and effectiveness of our novel method in a prototype application considering polished brass plates. Our results demonstrate a promising direction for surface parameter measurement in less restricted polishing process environments.

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