Visual inspection of products: a comparison of the methods used to evaluate surface anomalies
This paper presents and compares different approaches currently used to assess surface anomalies identified on a product. The common point between these methods is that they are based on a document presented in the form of a table, which is to help the inspector to assess the anomaly detected in a r...
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2011-01-01
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Online Access: | https://www.metrology-journal.org/articles/ijmqe/pdf/2011/01/ijmqe2011006.pdf |
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doaj-02395470854346f29dd19c0d85edf74f2021-09-21T15:17:23ZengEDP SciencesInternational Journal of Metrology and Quality Engineering2107-68392107-68472011-01-0121313810.1051/ijmqe/2011006ijmqe2011006Visual inspection of products: a comparison of the methods used to evaluate surface anomaliesBaudet N.Pillet M.Maire J.L.This paper presents and compares different approaches currently used to assess surface anomalies identified on a product. The common point between these methods is that they are based on a document presented in the form of a table, which is to help the inspector to assess the anomaly detected in a repeatable and reproducible way. We will present three types of table: criteria/level table, tree-like presentation table and an indexed table. As each of these tables presents certain limits when applied to the inspection of a product surface, we will describe the table proposed in order to help the inspector determine the intensity to attribute to the identified anomaly.https://www.metrology-journal.org/articles/ijmqe/pdf/2011/01/ijmqe2011006.pdfsurface anomalyvisual inspectionevaluation tablesensorial analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Baudet N. Pillet M. Maire J.L. |
spellingShingle |
Baudet N. Pillet M. Maire J.L. Visual inspection of products: a comparison of the methods used to evaluate surface anomalies International Journal of Metrology and Quality Engineering surface anomaly visual inspection evaluation table sensorial analysis |
author_facet |
Baudet N. Pillet M. Maire J.L. |
author_sort |
Baudet N. |
title |
Visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
title_short |
Visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
title_full |
Visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
title_fullStr |
Visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
title_full_unstemmed |
Visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
title_sort |
visual inspection of products: a comparison of the methods used to evaluate surface anomalies |
publisher |
EDP Sciences |
series |
International Journal of Metrology and Quality Engineering |
issn |
2107-6839 2107-6847 |
publishDate |
2011-01-01 |
description |
This paper presents and compares different approaches currently used to assess surface anomalies identified on a product. The common point between these methods is that they are based on a document presented in the form of a table, which is to help the inspector to assess the anomaly detected in a repeatable and reproducible way. We will present three types of table: criteria/level table, tree-like presentation table and an indexed table. As each of these tables presents certain limits when applied to the inspection of a product surface, we will describe the table proposed in order to help the inspector determine the intensity to attribute to the identified anomaly. |
topic |
surface anomaly visual inspection evaluation table sensorial analysis |
url |
https://www.metrology-journal.org/articles/ijmqe/pdf/2011/01/ijmqe2011006.pdf |
work_keys_str_mv |
AT baudetn visualinspectionofproductsacomparisonofthemethodsusedtoevaluatesurfaceanomalies AT pilletm visualinspectionofproductsacomparisonofthemethodsusedtoevaluatesurfaceanomalies AT mairejl visualinspectionofproductsacomparisonofthemethodsusedtoevaluatesurfaceanomalies |
_version_ |
1717372316370862080 |