Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components
Defects such as cracks, overlaps and impressions are prevalent in the manufacturing of press-hardened automotive body components. The prevailing industrial practices rely on manual visual inspections, which are both costly and less effective, thereby posing a risk of undetected defects. To address t...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
|
| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2025/02/matecconf_iddrg2025_01088.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849730710516006912 |
|---|---|
| author | Simon Fabio Werner Thomas Weidemann Andreas Guilleaume Christina Brosius Alexander |
| author_facet | Simon Fabio Werner Thomas Weidemann Andreas Guilleaume Christina Brosius Alexander |
| author_sort | Simon Fabio |
| collection | DOAJ |
| description | Defects such as cracks, overlaps and impressions are prevalent in the manufacturing of press-hardened automotive body components. The prevailing industrial practices rely on manual visual inspections, which are both costly and less effective, thereby posing a risk of undetected defects. To address these challenges, the potential of smart vision sensors for automated component inspection is being investigated. A dedicated test rig was constructed for the purpose of studying the key influencing factors on the output similarity values of the image processing system. These factors include the temperature of the component subsequent to the processing stage and the exposure to the light conditions during the inspection. The performance of the system was evaluated using confusion matrices in order to assess precision and repeatability. For the deformation and crack defect types discrepancies were not observed between the actual and predicted classifications. For the purpose of a practical acceptance of the test system, a left-tailed hypothesis test is carried out for the overlap defect type. The results of the study demonstrate the potential of inspection systems to improve accurate defect detection, thereby paving the way for their implementation in production environments. |
| format | Article |
| id | doaj-art-1ecb1aaba7a34fdbb69fab5c76c38057 |
| institution | DOAJ |
| issn | 2261-236X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj-art-1ecb1aaba7a34fdbb69fab5c76c380572025-08-20T03:08:47ZengEDP SciencesMATEC Web of Conferences2261-236X2025-01-014080108810.1051/matecconf/202540801088matecconf_iddrg2025_01088Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body componentsSimon Fabio0Werner Thomas1Weidemann Andreas2Guilleaume Christina3Brosius Alexander4TUD Dresden University of Technology, Chair of Forming and Machining TechnologyTUD Dresden University of Technology, Chair of Forming and Machining TechnologyMAGNA International Stanztechnik GmbHTUD Dresden University of Technology, Chair of Forming and Machining TechnologyTUD Dresden University of Technology, Chair of Forming and Machining TechnologyDefects such as cracks, overlaps and impressions are prevalent in the manufacturing of press-hardened automotive body components. The prevailing industrial practices rely on manual visual inspections, which are both costly and less effective, thereby posing a risk of undetected defects. To address these challenges, the potential of smart vision sensors for automated component inspection is being investigated. A dedicated test rig was constructed for the purpose of studying the key influencing factors on the output similarity values of the image processing system. These factors include the temperature of the component subsequent to the processing stage and the exposure to the light conditions during the inspection. The performance of the system was evaluated using confusion matrices in order to assess precision and repeatability. For the deformation and crack defect types discrepancies were not observed between the actual and predicted classifications. For the purpose of a practical acceptance of the test system, a left-tailed hypothesis test is carried out for the overlap defect type. The results of the study demonstrate the potential of inspection systems to improve accurate defect detection, thereby paving the way for their implementation in production environments.https://www.matec-conferences.org/articles/matecconf/pdf/2025/02/matecconf_iddrg2025_01088.pdfpress hardeningdigital image processingsmart vision sensorsautomated inspection |
| spellingShingle | Simon Fabio Werner Thomas Weidemann Andreas Guilleaume Christina Brosius Alexander Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components MATEC Web of Conferences press hardening digital image processing smart vision sensors automated inspection |
| title | Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components |
| title_full | Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components |
| title_fullStr | Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components |
| title_full_unstemmed | Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components |
| title_short | Investigation of a test rig based on smart vision sensors for automated inspection of press-hardened automotive body components |
| title_sort | investigation of a test rig based on smart vision sensors for automated inspection of press hardened automotive body components |
| topic | press hardening digital image processing smart vision sensors automated inspection |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2025/02/matecconf_iddrg2025_01088.pdf |
| work_keys_str_mv | AT simonfabio investigationofatestrigbasedonsmartvisionsensorsforautomatedinspectionofpresshardenedautomotivebodycomponents AT wernerthomas investigationofatestrigbasedonsmartvisionsensorsforautomatedinspectionofpresshardenedautomotivebodycomponents AT weidemannandreas investigationofatestrigbasedonsmartvisionsensorsforautomatedinspectionofpresshardenedautomotivebodycomponents AT guilleaumechristina investigationofatestrigbasedonsmartvisionsensorsforautomatedinspectionofpresshardenedautomotivebodycomponents AT brosiusalexander investigationofatestrigbasedonsmartvisionsensorsforautomatedinspectionofpresshardenedautomotivebodycomponents |