Optical Quality Control for Adaptive Polishing Processes

verfasst von

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

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.

Organisationseinheit(en)

PhoenixD: Simulation, Fabrikation und Anwendung optischer Systeme
Institut für Fertigungstechnik und Werkzeugmaschinen

Externe Organisation(en)

Technische Universität Braunschweig
University of New Mexico

Typ

Aufsatz in Konferenzband

Seiten

90-94

Anzahl der Seiten

5

Publikationsdatum

2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Software, Maschinelles Sehen und Mustererkennung, Angewandte Informatik

Elektronische Version(en)

https://doi.org/10.1109/ssiai49293.2020.9094615 (Zugang: Geschlossen)