A Hybrid Force-Directed Self-Organizing Neural Network Approach to Automatic Printed Circuit Board Component Placement with EMC Consideration

Teck Lin ANG  Yuji TARUI  Takashi SAKUSABE  Takehiro TAKAHASHI  Noboru SCHIBUYA  

Publication
IEICE TRANSACTIONS on Communications   Vol.E85-B   No.9   pp.1797-1805
Publication Date: 2002/09/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8516
Type of Manuscript: PAPER
Category: Electromagnetic Compatibility(EMC)
Keyword: 
EMC,  PCB,  force-directed method,  placement,  neural network,  

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Summary: 
This paper describes a hybrid force-directed self-organizing neural network approach to printed circuit board (PCB) placement with consideration of electromagnetic compatibility (EMC). In most of the conventional PCB automatic placement algorithms, the only factor considered in the objective function is minimized total net length. However, for today's high speed and high density PCB, EMC compliance cannot be met by such single objective. To tackle this problem, the presented algorithm takes EMC into consideration, besides component overlap and minimized total net length. These factors are optimized by means of an adapted self-organizing map. Comparison of simulated placement results as well as actual measurements with commercial softwares confirms the effectiveness of the proposed method.