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Proceedings Paper

Feasibility of automating printed circuit board assembly using artificial neural networks
Author(s): Cihan H. Dagli; Mahesh K. Vellanki
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Paper Abstract

In this study automation of circuit board assembly process is considered using artificial neural networks with knowledge based systems. Basic issues of achieving intelligent conirol that can adopt to changing conditions of assembly process are discussed. The feasibility of using neural networks for pattern recognition and optimum kit insertion sequence generation is examined. The study provides a basic foundation for designing a conceptual architecture for adaptive intelligent control of circuit board assembly. Component recognition section of the architecture is tested using an ART network based on real time images and promising results are obtained. 1.

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21185
Show Author Affiliations
Cihan H. Dagli, Univ. of Missouri/Rolla (United States)
Mahesh K. Vellanki, Univ. of Missouri/Rolla (United States)


Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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