JOURNAL ARTICLE

Automatic Optical Inspection of Printed Circuit Boards

K.G. Doyle

Year: 1984 Journal:   Circuit World Vol: 11 (1)Pages: 38-40   Publisher: Emerald Publishing Limited

Abstract

An automatic optical printed circuit board inspection machine will be described which provides considerable improvements on existing methods of PCB inspection and testing. The machine can detect breaks, nicks, shorts, pinholes, inadequate track clearances, inadequate track widths and holes which are undersized, oversized, missing or not concentric with the pad. It can be used in a non‐comparison mode to detect small defects in boards or photographic negatives, and can also be used in a comparison mode to provide a complete functional test of a board similar to that provided by a bed‐of‐nails tester, but with improved detection of marginal faults. The board is optically scanned and the resulting large amounts of data are reduced by special hardware and software techniques which allow rapid throughput and virtually eliminate ‘false alarms’ caused by lettering, logos, dust specks etc. which do not affect the functionality of the board. This technique differs considerably from the ‘Feature recognition’ and the ‘Comparison’ techniques at present employed in automatic optical PCB inspection. Operation of the machine is very simple as the board does not need to be accurately positioned, and a simple ‘good/bad’ indication is provided as well as more detailed defect location information.

Keywords:
Printed circuit board Automated optical inspection Feature (linguistics) Computer hardware Engineering Track (disk drive) Software Lettering Automated X-ray inspection Computer science Engineering drawing Artificial intelligence Image processing Electrical engineering Mechanical engineering Image (mathematics)

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3
Cited By
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FWCI (Field Weighted Citation Impact)
0
Refs
0.16
Citation Normalized Percentile
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Citation History

Topics

Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Integrated Circuits and Semiconductor Failure Analysis
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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