Development Of Software System For Detecting Defective Symbol On IC Chip Using Matrox Imaging Library
In semiconductor fabrication process, symbol or label inspection is one of the main processes that needs to be considered seriously. Errors may occur during the printing process of label or name on the integrated circuit chip (IC). If this occurs, the IC chip may have a wrong name. This will affe...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/5945/1/FK_2004_49%20IR.pdf |
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| Summary: | In semiconductor fabrication process, symbol or label inspection is one of the main
processes that needs to be considered seriously. Errors may occur during the printing
process of label or name on the integrated circuit chip (IC). If this occurs, the IC chip
may have a wrong name. This will affect the credibility of the company who produces
the IC chips. The problem mentioned above can be solved by providing a reliable
detection system that is able to detect the errors printed on the IC chip.
The symbol detection system that currently being implemented by the semiconductor
industry suffers from over killed and escapes problems. This project presents the
development a software system, which capable of detecting the defective characters
printed on the IC chip using Active Matrox Imaging Library Release 7. The proposed system has an adjustable reading level that can solve the overkilled and escaped
problems. It consists of a graphical user interface module, an inference engine, an image
database, an ActiveMIL ActiveX control module, a Matrox Imaging Library module, an
input image, and an output image. The proposed system is written in Visual Basic
version 6 and it is interfaced with Active Matrox Imaging Library.
The proposed system also has learning capability. It can store up to two different IC
images at one time. The system was designed for off-line operation. The test results
demonstrated that the proposed system performs according to its functions. It achieves
100% detection rate. |
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