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Proceedings Paper

Neural networks based AOI systems for electronic devices diagnosis
Author(s): Mario Lera; A. Montisci
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Paper Abstract

In this work an Automatic Optical Inspection (AOI) system has been developed to diagnose Printed Circuit Boards (PCB) mounted in Surface Mounting Technology (SMT). The diagnosis task is handled as a classification problem with a neural network approach. We will present results on the diagnosis of visible defects on a SMT-PCB. A CCD camera acquires a number of images of the circuit under test and a neural network associates these images to a defect class. A set of procedures makes automatic the set-up and the diagnosis phases. The developed system seems to be a good solution in an industrial application because of the low cost, very fast diagnosis and easiness to set-up and handle.

Paper Details

Date Published: 19 November 2003
PDF: 3 pages
Proc. SPIE 4829, 19th Congress of the International Commission for Optics: Optics for the Quality of Life, (19 November 2003); doi: 10.1117/12.530952
Show Author Affiliations
Mario Lera, Univ. degli Studi di Cagliari (Italy)
A. Montisci, Univ. degli Studi di Cagliari (Italy)


Published in SPIE Proceedings Vol. 4829:
19th Congress of the International Commission for Optics: Optics for the Quality of Life
Giancarlo C. Righini; Anna Consortini, Editor(s)

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