Recipe generation of under fill process based on improved kernel regression and particle swarm optimization

The under fill process is a process that fills the gap between a chipset and a substrate using an epoxy material. The output of this process is a length of tongue that has to be controlled so it avoid touching the keep out zone. A recipe generation of the input parameters in the under fill process w...

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Main Author: Othman, Mohd. Hafiz
Format: Thesis
Language:English
Published: 2012
Subjects:
Online Access:http://eprints.utm.my/id/eprint/33404/5/MohdHafizOthmanMFKE2012.pdf
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spelling my-utm-ep.334042018-05-27T08:07:43Z Recipe generation of under fill process based on improved kernel regression and particle swarm optimization 2012-01 Othman, Mohd. Hafiz TK Electrical engineering. Electronics Nuclear engineering The under fill process is a process that fills the gap between a chipset and a substrate using an epoxy material. The output of this process is a length of tongue that has to be controlled so it avoid touching the keep out zone. A recipe generation of the input parameters in the under fill process will help the length of tongue generated from touching the keep out zone. This project proposes a predictive modeling algorithm called Improved Kernel Regression and Particle Swarm Optimization in order to find the six input parameters needed in the under fill process. Even though only few samples of the under fill data sets are used in the simulation experiment, the proposed approach is able to provide a recipe generation of the six input parameters. 2012-01 Thesis http://eprints.utm.my/id/eprint/33404/ http://eprints.utm.my/id/eprint/33404/5/MohdHafizOthmanMFKE2012.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:70202?site_name=Restricted Repository 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
Othman, Mohd. Hafiz
Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
description The under fill process is a process that fills the gap between a chipset and a substrate using an epoxy material. The output of this process is a length of tongue that has to be controlled so it avoid touching the keep out zone. A recipe generation of the input parameters in the under fill process will help the length of tongue generated from touching the keep out zone. This project proposes a predictive modeling algorithm called Improved Kernel Regression and Particle Swarm Optimization in order to find the six input parameters needed in the under fill process. Even though only few samples of the under fill data sets are used in the simulation experiment, the proposed approach is able to provide a recipe generation of the six input parameters.
format Thesis
qualification_level Master's degree
author Othman, Mohd. Hafiz
author_facet Othman, Mohd. Hafiz
author_sort Othman, Mohd. Hafiz
title Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
title_short Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
title_full Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
title_fullStr Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
title_full_unstemmed Recipe generation of under fill process based on improved kernel regression and particle swarm optimization
title_sort recipe generation of under fill process based on improved kernel regression and particle swarm optimization
granting_institution Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department Faculty of Electrical Engineering
publishDate 2012
url http://eprints.utm.my/id/eprint/33404/5/MohdHafizOthmanMFKE2012.pdf
_version_ 1747816153031376896