A real time marking inspection scheme for semiconductor industries

In this paper, a real time industrial machine vision system incorporating optical character recognition (OCR) is employed to inspect markings on integrated circuit (IC) chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from...

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Main Authors: Nagarajan, R., Yaacob, Sazali, Pandian, P., Karthigayan, M., Amin, Shamsudin, Khalid, Marzuki
Format: Article
Language:English
Published: Springer 2007
Subjects:
Online Access:http://eprints.utm.my/id/eprint/7203/1/ShamsudinHjAmin2007_%20Arealtimemarkinginspectionscheme.pdf
http://eprints.utm.my/id/eprint/7203/
http://dx.doi.org/10.1007/s00170-006-0669-1
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spelling my.utm.72032017-03-14T08:58:19Z http://eprints.utm.my/id/eprint/7203/ A real time marking inspection scheme for semiconductor industries Nagarajan, R. Yaacob, Sazali Pandian, P. Karthigayan, M. Amin, Shamsudin Khalid, Marzuki TJ Mechanical engineering and machinery In this paper, a real time industrial machine vision system incorporating optical character recognition (OCR) is employed to inspect markings on integrated circuit (IC) chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from Texas Instruments is used in the investigation. The IC chip markings are laser printed. This inspection system tests whether the laser printed marking on IC chips is proper. The inspection has to identify print errors such as illegible characters, missing characters and upside down printing. The vision inspection of the printed markings on the IC chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. The MATLAB platform and its toolboxes are used for designing the inspection processing technique. Speed of the marking inspection is mostly dependent on the effectiveness of the feature extraction technique. The performances of four feature extraction techniques are compared in terms of their respective speed. The feature extracted data are used in a neural network for classifying the marking errors. A suggestion to optimize the number of input neurons of the neural network for a fast classification is also presented. Springer 2007-10 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/7203/1/ShamsudinHjAmin2007_%20Arealtimemarkinginspectionscheme.pdf Nagarajan, R. and Yaacob, Sazali and Pandian, P. and Karthigayan, M. and Amin, Shamsudin and Khalid, Marzuki (2007) A real time marking inspection scheme for semiconductor industries. The international journal of advanced manufacturing technology, 34 (9-10). pp. 926-932. ISSN 0268-3768 (Print) 1433-3015 (Online) http://dx.doi.org/10.1007/s00170-006-0669-1 10.1007/s00170-006-0669-1
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Nagarajan, R.
Yaacob, Sazali
Pandian, P.
Karthigayan, M.
Amin, Shamsudin
Khalid, Marzuki
A real time marking inspection scheme for semiconductor industries
description In this paper, a real time industrial machine vision system incorporating optical character recognition (OCR) is employed to inspect markings on integrated circuit (IC) chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from Texas Instruments is used in the investigation. The IC chip markings are laser printed. This inspection system tests whether the laser printed marking on IC chips is proper. The inspection has to identify print errors such as illegible characters, missing characters and upside down printing. The vision inspection of the printed markings on the IC chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. The MATLAB platform and its toolboxes are used for designing the inspection processing technique. Speed of the marking inspection is mostly dependent on the effectiveness of the feature extraction technique. The performances of four feature extraction techniques are compared in terms of their respective speed. The feature extracted data are used in a neural network for classifying the marking errors. A suggestion to optimize the number of input neurons of the neural network for a fast classification is also presented.
format Article
author Nagarajan, R.
Yaacob, Sazali
Pandian, P.
Karthigayan, M.
Amin, Shamsudin
Khalid, Marzuki
author_facet Nagarajan, R.
Yaacob, Sazali
Pandian, P.
Karthigayan, M.
Amin, Shamsudin
Khalid, Marzuki
author_sort Nagarajan, R.
title A real time marking inspection scheme for semiconductor industries
title_short A real time marking inspection scheme for semiconductor industries
title_full A real time marking inspection scheme for semiconductor industries
title_fullStr A real time marking inspection scheme for semiconductor industries
title_full_unstemmed A real time marking inspection scheme for semiconductor industries
title_sort real time marking inspection scheme for semiconductor industries
publisher Springer
publishDate 2007
url http://eprints.utm.my/id/eprint/7203/1/ShamsudinHjAmin2007_%20Arealtimemarkinginspectionscheme.pdf
http://eprints.utm.my/id/eprint/7203/
http://dx.doi.org/10.1007/s00170-006-0669-1
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score 13.160551