Universiti Teknologi Malaysia Institutional Repository

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

Othman, Mohd. Hafiz (2012) Recipe generation of under fill process based on improved kernel regression and particle swarm optimization. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

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Abstract

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.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Mekatronik dan Kawalan Automatik)) - Universiti Teknologi Malaysia, 2012; Supervisor : Dr. Zuwairie Ibrahim
Uncontrolled Keywords:kernel regression, particle swarm optimization, recipe generation
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:33404
Deposited By: Narimah Nawil
Deposited On:25 Oct 2013 00:43
Last Modified:27 May 2018 08:07

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