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The development of an artificial neural network embedded automated inspection quality management system

This paper describes in detail the development of an innovative artificial neural network embedded automated inspection scheme for the manufacturing industry employing digital image processing techniques. Such a system is capable of performing real-time image processing tasks and identifies the size...

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Bibliographic Details
Main Authors: Chih-Hsien Kung, Devaney, M.J., Chung-Ming Huang, Chih-Ming Kung, Yi-Jen Wang
Format: Conference Proceeding
Language:English
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Summary:This paper describes in detail the development of an innovative artificial neural network embedded automated inspection scheme for the manufacturing industry employing digital image processing techniques. Such a system is capable of performing real-time image processing tasks and identifies the size and location of the finished components on manufactured products as well as the flaws and scratches on surface of products during the manufacturing process. The proposed artificial neural network embedded quality management system provides a user-friendly user interface that has been implemented and tested on a case study from a printed circuit board manufacture. The experimental results have demonstrated the functionality and superiority of the developed artificial neural network embedded inspection system.
ISSN:1091-5281
DOI:10.1109/IMTC.2001.928200