Feasibility of automating printed circuit board assembly using artificial neural networks

Cihan H. Dagli; Mahesh K. Vellanki

doi:10.1117/12.21185

1 August 1990 Feasibility of automating printed circuit board assembly using artificial neural networks

Cihan H. Dagli, Mahesh K. Vellanki

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21185
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

Citation Download Citation

Cihan H. Dagli and Mahesh K. Vellanki "Feasibility of automating printed circuit board assembly using artificial neural networks", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21185

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