Implementation of Machine Vision based Quality Inspection in Production: An Approach for the Accelerated Execution of Case Studies
Reichenstein T, Raffin T, Sand C, Franke J (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Original Authors: Tobias Reichenstein, Tim Raffin, Christian Sand, Jörg Franke
Book Volume: 112
Pages Range: 596-601
DOI: 10.1016/j.procir.2022.09.058
Abstract
The implementation of machine vision based quality inspection systems increases productivity and reduces human error during visual inspection, thus improving product quality. During the planning process of these inspection systems, case studies are executed to evaluate and ensure applicability, which so far has been an iterative and inefficient process due to the lack of existing methodologies and guidelines. Therefore, this paper presents a holistic approach for efficiently executing case studies to plan and implement machine vision based quality inspection systems in production. An evaluation via an industrial use-case resulted in a significantly quicker planning process.
Authors with CRIS profile
Tobias Reichenstein
Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik
Tim Raffin
Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik
Jörg Franke
Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik
Related research project(s)
Involved external institutions
Germany (DE)How to cite
APA:
Reichenstein, T., Raffin, T., Sand, C., & Franke, J. (2022). Implementation of Machine Vision based Quality Inspection in Production: An Approach for the Accelerated Execution of Case Studies. Procedia CIRP, 112, 596-601. https://dx.doi.org/10.1016/j.procir.2022.09.058
MLA:
Reichenstein, Tobias, et al. "Implementation of Machine Vision based Quality Inspection in Production: An Approach for the Accelerated Execution of Case Studies." Procedia CIRP 112 (2022): 596-601.
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