Visual quality prediction of plastic product based on thermographic images
LE GOFF Ronan, MARCHAL Nils, AGAZZI Alban
download PDFAbstract. The main purpose of this study is to control the visual quality in plastic injection moulding using an infrared camera after the ejection of the plastic part. Quality indicators have been extracted from the thermal image and from the data recorded by the sensors in the plastic injection machine and in the mould. After cooling, visual quality has been labelled by plastic experts based on 3 aesthetic defects: spot, flow line and streak mark. Three methods of reducing the dimension of the thermal image were studied: Quantiles, Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA). The visual quality can be predicted efficiently using dimension reduction of the image and Partial Least Square (PLS) regression. The PLS results allow to identify the root causes that explain the apparition of visual defects.
Keywords
Injection Moulding, Quality Prediction, Thermography
Published online 4/19/2023, 10 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: LE GOFF Ronan, MARCHAL Nils, AGAZZI Alban, Visual quality prediction of plastic product based on thermographic images, Materials Research Proceedings, Vol. 28, pp 1565-1574, 2023
DOI: https://doi.org/10.21741/9781644902479-169
The article was published as article 169 of the book Material Forming
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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