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Title:Adaptive visual quality inspection based on defect prediction from production parameters
Authors:ID Lončarević, Zvezdan, Institut Jožef Stefan (Author)
ID Reberšek, Simon, Institut Jožef Stefan (Author)
ID Šela, Samo (Author)
ID Skvarč, Jure (Author)
ID Ude, Aleš, Institut Jožef Stefan (Author)
ID Gams, Andrej, Institut Jožef Stefan (Author)
Files:URL URL - Source URL, visit https://ieeexplore.ieee.org/document/10587254
 
.pdf PDF - Presentation file, download (7,44 MB)
MD5: B6EFFB21439897CD974B52FF26B6C1CD
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo IJS - Jožef Stefan Institute
Abstract:At the end of a production process, the manufactured products must usually be visually inspected to ensure their quality. Often, it is necessary to inspect the final product from several viewpoints. However, the inspection of all possible aspects might take too long and thus create a bottleneck in the production process. In this paper we propose and evaluate a methodology for adaptive, robot-aided visual quality inspection. With the proposed method, the most probable defects are first predicted based on the production process parameters. A suitable classifier for defect prediction is learnt in an unsupervised manner from a database that includes the produced parts and the associated parameters.Arobot then steers the camera only towards viewpoints associated with predicted defects, which implies that the trajectories of robot motion for the inspection might be different for every product. To enable dynamic planning of camera trajectories, we describe a methodology for evaluation and selection of the most appropriate autonomous motion planner. The proposed defect prediction approach was compared to other methods and evaluated on the products from a real-world production line for injection moulding, which was implemented for a producer of parts in the automotive industry.
Keywords:robot learning, robotic quality inspection, visual quality inspection, injection moulding, production parameters, robot motion planning
Publication status:In print
Publication version:Author Accepted Manuscript
Publication date:08.07.2024
Publisher:IEEE
Year of publishing:2024
Number of pages:str. 1-12
Numbering:Vol. 12
Source:ZDA
PID:20.500.12556/DiRROS-19297 New window
UDC:007.52
ISSN on article:2169-3536
DOI:10.1109/ACCESS.2024.3424664 New window
COBISS.SI-ID:201318659 New window
Note:Nasl. z nasl. zaslona; Soavtorji: Simon Reberšek, Samo Šela, Jure Skvarč, Aleš Ude, Andrej Gams; Opis vira z dne 10. 7. 2024;
Publication date in DiRROS:15.07.2024
Views:342
Downloads:230
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Record is a part of a journal

Title:IEEE access
Publisher:Institute of Electrical and Electronics Engineers
ISSN:2169-3536
COBISS.SI-ID:519839513 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0076
Name:Avtomatika, Robotika in Biokibernetika

Funder:Other - Other funder or multiple funders
Funding programme:Ministry of Higher Education, Science and Innovation of Slovenia, Slovenian Research and Innovation Agency and European Union – NextGenerationEU
Acronym:DIGITOP

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:08.07.2024

Secondary language

Language:Slovenian
Keywords:vizualni nadzor kakovosti


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