Multidisciplinary placement optimization of heat generating electronic components on printed circuit boards

Tohru Suwa, Hamid Hadim

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

A multidisciplinary placement optimization methodology for heat generating electronic components on printed circuit boards (PCBs) is presented. The methodology includes thermal, electrical, and placement criteria involving junction temperature, wiring density, line length for high frequency signals, and critical component location which are optimized simultaneously using the genetic algorithm. A board-level thermal performance prediction methodology which is based on a combination of a superposition method and artificial neural networks is developed for this study. Two genetic algorithms with different thermal prediction modules are used in a cascade in the optimization process. The first genetic algorithm uses simplified thermal network modeling and it is mainly aimed at finding component locations that avoid any overlap. Compact thermal models are used in the second genetic algorithm leading to more accurate thermal prediction which improves the placement optimization obtained using the first algorithm. Using this optimization methodology, large calculation time reduction is achieved without losing accuracy. To demonstrate its capabilities, the present methodology is applied to a test case involving placement optimization of several heat generating electronics components on a PCB.

Original languageEnglish
Pages (from-to)90-97
Number of pages8
JournalJournal of Electronic Packaging, Transactions of the ASME
Volume129
Issue number1
DOIs
StatePublished - Mar 2007

Keywords

  • Artificial neural networks application
  • Electronic component placement
  • Genetic algorithm application

Fingerprint

Dive into the research topics of 'Multidisciplinary placement optimization of heat generating electronic components on printed circuit boards'. Together they form a unique fingerprint.

Cite this