Automated CAD-based sensor planning and system implementation for assembly supervision

Journal
Procedia CIRP  
Volume
118
Start Page
930
End Page
934
Citation
Conference 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering - Procedia CIRP 118: 930-934 (2023)
Contribution to Conference
16th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2022  
Publisher DOI
10.1016/j.procir.2023.06.160
Scopus ID
2-s2.0-85173577544
Publisher
Elsevier B.V.
Industrial manual assembly, especially within the area of large-scale assembly, often lacks process monitoring since the feedback about performed assembly tasks is only generated by the worker. Optical sensor systems thereby offer the potential to monitor assembly states automatically and derive the required information without intervening the work in progress. With the growing trend of customization, not only the assembly process itself, but also the monitoring system must be adapt- able at short notice. However, most machine vision systems, as they are today, are commonly task-specific solutions and are therefore hard to be transferred to another inspection task or other work objects. To lower the barriers on applying machine vision into varying environments, this paper introduces an automated CAD-based sensor planning and implementation pipeline. An analysis and derivation of common constraints in assembly design is laid out, followed by a method of generating and optimizing inspection features and sensor poses. A strategy to implement the image processing pipeline based on the derived features is presented and applied on an assembly use case.
Subjects
assembly
flexible automation
industry 4.0
vision systems
sensor planning
DDC Class
600: Technology
Lizenz
https://creativecommons.org/licenses/by-nc-nd/4.0/
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