Title of article
Artificial Intelligence Techniques In IC Chip Marking Inspection
Author/Authors
KARTHIGAYAN, M. Kolej Universiti Kejuruteraan Utara Malaysia - School of Mechatronics, Malaysia , NAGARAJAN, R. Kolej Universiti Kejuruteraan Utara Malaysia - School of Mechatronics, Malaysia , YAACOB, SAZALI Kolej Universiti Kejuruteraan Utara Malaysia - School of Mechatronics, Malaysia , PANDIAN, PAULRAJ Kolej Universiti Kejuruteraan Utara Malaysia - School of Mechatronics, Malaysia , RIZON, MOHAMED Kolej Universiti Kejuruteraan Utara Malaysia - School of Mechatronics, Malaysia
From page
17
To page
29
Abstract
In this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the 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 Instrument is used in this investigation. The IC chips markings are laser printed. This inspection system tests are laser printed marking on IC chips and are according to the specifications. Artificial intelligence (Al) techniques are used in this inspection. Al techniques utilized are neural network and fuzzy logic. The inspection is carried out to find the print errors; such as illegible character, upside down print and missing characters. The vision inspection of the printed markings on the IC chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. MATLAB platform and its toolboxes are used for designing the inspection processing technique. The percentage of accuracy of the classification is found to be between 97% - 100%.
Journal title
Journal of Engineering Research and Education
Journal title
Journal of Engineering Research and Education
Record number
2695655
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