Thermal and area optimization for component placement on PCB design using inverse genetic algorithm

Considering the current trend of compact designs which are mostly multiobjective in nature, proper arrangement of components has become a basic necessity so as to have optimal management of heat generation and dissipation. In this work, Inverse Genetic Algorithm (IGA) optimization has been adopted i...

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Main Author:	Abubakar, Abubakar Kamal
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/78673/1/AbubakarKamalAbubakarMFKE2015.pdf
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spelling	my-utm-ep.786732018-08-29T07:56:43Z Thermal and area optimization for component placement on PCB design using inverse genetic algorithm 2015-12 Abubakar, Abubakar Kamal TK Electrical engineering. Electronics Nuclear engineering Considering the current trend of compact designs which are mostly multiobjective in nature, proper arrangement of components has become a basic necessity so as to have optimal management of heat generation and dissipation. In this work, Inverse Genetic Algorithm (IGA) optimization has been adopted in order to achieve optimal placement of components on printed circuit board (PCB). The objective functions are the PCB area and temperature of each component while the constraint parameters are; to avoid the overlapping of components, the maximum allowable PCB area is 2(120193.4)mm2 , thermal connections were internally set, and the manufacturer allowable temperature for the ICs must be more than the components optimal temperature. In the conventional Forward Genetic Algorithm (FGA) optimization, the individual fitness of components are generated through the GA process. The IGA approach on the other hand, allows the user to set the desired fitness, so that the GA process will try to approach these set values. Hence, the IGA has two major advantages over FGA; the first being a reduction in the overall computational time and the other is the freedom of choosing the desired fitness (i.e. ability to manipulate the GA output). The objectives of this work includes; development of an IGA search Engine, minimization of the thermal profile of components based on thermal resistance network and the area of PCB, and comparison of the proposed IGA and FGA performances. From the simulation results, the IGA has successfully minimized the thermal profile and area of PCB by 0.78% and 1.28% respectively. The CPU-time has also been minimised by 15.56%. 2015-12 Thesis http://eprints.utm.my/id/eprint/78673/ http://eprints.utm.my/id/eprint/78673/1/AbubakarKamalAbubakarMFKE2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106121 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Abubakar, Abubakar Kamal Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
description	Considering the current trend of compact designs which are mostly multiobjective in nature, proper arrangement of components has become a basic necessity so as to have optimal management of heat generation and dissipation. In this work, Inverse Genetic Algorithm (IGA) optimization has been adopted in order to achieve optimal placement of components on printed circuit board (PCB). The objective functions are the PCB area and temperature of each component while the constraint parameters are; to avoid the overlapping of components, the maximum allowable PCB area is 2(120193.4)mm2 , thermal connections were internally set, and the manufacturer allowable temperature for the ICs must be more than the components optimal temperature. In the conventional Forward Genetic Algorithm (FGA) optimization, the individual fitness of components are generated through the GA process. The IGA approach on the other hand, allows the user to set the desired fitness, so that the GA process will try to approach these set values. Hence, the IGA has two major advantages over FGA; the first being a reduction in the overall computational time and the other is the freedom of choosing the desired fitness (i.e. ability to manipulate the GA output). The objectives of this work includes; development of an IGA search Engine, minimization of the thermal profile of components based on thermal resistance network and the area of PCB, and comparison of the proposed IGA and FGA performances. From the simulation results, the IGA has successfully minimized the thermal profile and area of PCB by 0.78% and 1.28% respectively. The CPU-time has also been minimised by 15.56%.
format	Thesis
qualification_level	Master's degree
author	Abubakar, Abubakar Kamal
author_facet	Abubakar, Abubakar Kamal
author_sort	Abubakar, Abubakar Kamal
title	Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
title_short	Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
title_full	Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
title_fullStr	Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
title_full_unstemmed	Thermal and area optimization for component placement on PCB design using inverse genetic algorithm
title_sort	thermal and area optimization for component placement on pcb design using inverse genetic algorithm
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utm.my/id/eprint/78673/1/AbubakarKamalAbubakarMFKE2015.pdf
_version_	1747818043278360576

Thermal and area optimization for component placement on PCB design using inverse genetic algorithm

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