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Spatio-temporal adaptive sampling for effective coverage measurement planning during quality inspection of free form surfaces using robotic 3D optical scanner
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Babu, Manoj, Franciosa, Pasquale and Ceglarek, Dariusz (2019) Spatio-temporal adaptive sampling for effective coverage measurement planning during quality inspection of free form surfaces using robotic 3D optical scanner. Journal of Manufacturing Systems, 53 . pp. 93-108. doi:10.1016/j.jmsy.2019.08.003
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Official URL: http://dx.doi.org/10.1016/j.jmsy.2019.08.003
Abstract
In-line dimensional inspection of free form surfaces using robotic 3D-optical scanners provide an opportunity to reduce the mean-time-to-detection of product quality defects and has thus emerged as a critical enabler in Industry 4.0 to achieve near-zero defects. However, the time needed to inspect large industrial size sheet metal parts by 3D-optical scanners frequently exceeds the production cycle time (CT), consequently, limiting the application of in-line measurement systems for high production volume manufacturing processes such as those used in the automotive industry. This paper addresses the aforementioned challenge by developing the Spatio-Temporal Adaptive Sampling (STAS) methodology which has the capability for (i) estimation of whole part deviations based on partial measurement of a free form surface; and, (ii) adaptive selection of the next region to be measured in order to satisfy pre-defined measurement criterion. This is achieved by first, modelling spatio-temporal correlations in the high dimensional Cloud-of-Points measurement data by using a dimension reduced space-time Kalman filter; then, dynamically updating the model parameters during the inspection process by incorporating partial measurement data to predict entire part deviations and adaptively choose the next critical region of the part to be measured.
| Item Type: | Journal Article | ||||||||||||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) T Technology > TS Manufactures |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Surfaces -- Areas and volumes, Three-dimensional printing , Spatial analysis (Statistics) | ||||||||||||||||||
| Journal or Publication Title: | Journal of Manufacturing Systems | ||||||||||||||||||
| Publisher: | Elsevier | ||||||||||||||||||
| ISSN: | 0278-6125 | ||||||||||||||||||
| Official Date: | October 2019 | ||||||||||||||||||
| Dates: |
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| Volume: | 53 | ||||||||||||||||||
| Page Range: | pp. 93-108 | ||||||||||||||||||
| DOI: | 10.1016/j.jmsy.2019.08.003 | ||||||||||||||||||
| Status: | Peer Reviewed | ||||||||||||||||||
| Publication Status: | Published | ||||||||||||||||||
| Access rights to Published version: | Open Access | ||||||||||||||||||
| RIOXX Funder/Project Grant: |
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