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A real time marking inspection scheme for semiconductor industries

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Abstract

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.

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Authors and Affiliations

  1. School of Mechatronics, Northern Malaysia University College of Engineering, 01000, Kangar, Malaysia

    R. Nagarajan, Sazali Yaacob, Paulraj Pandian & M. Karthigayan

  2. Center for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

    Shamsudin Hj Amin & Marzuki Khalid

Authors
  1. R. Nagarajan
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  2. Sazali Yaacob
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  3. Paulraj Pandian
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  4. M. Karthigayan
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  5. Shamsudin Hj Amin
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  6. Marzuki Khalid
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Corresponding author

Correspondence to M. Karthigayan.

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Nagarajan, R., Yaacob, S., Pandian, P. et al. A real time marking inspection scheme for semiconductor industries. Int J Adv Manuf Technol 34, 926–932 (2007). https://doi.org/10.1007/s00170-006-0669-1

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  • DOI: https://doi.org/10.1007/s00170-006-0669-1

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