Fairuz, Idris (2013) To study the multi-objective optimization of EDM using genetic algorithm. Faculty of Mechanical Engineering , Universiti Malaysia Pahang.
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Abstract
In the manufacturing industry, the production and quality of a product is very important, especially when it involves the big industries EDM. A machine such as EDM (electro discharge machine) used to produce a product that require an accurate product quality. EDM is one of the most accurate manufacturing processes for creating geometric shapes whether complex or simple in parts and assemblies. Development of EDM process has resulted in significant improvements in operating techniques, productivity and accuracy, which the result of this machining development has helped variability in EDM process. The main purpose of this study is to optimize the parameters used in EDM machining such as non-electrical parameter, electrical parameters, the characteristics of the machining, work piece and the variable parameters that will affect the actual machining performances such as material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). In the process of the study, the second- order mathematical model has been create as a fitness function using MATLAB software to generate multi-objective optimization responses using Genetic Algorithms, peak current, pulse-on time, pulse-off time and servo voltage are act as input of parameter setting. Based on the responses from EDM machining process which has been conducted showed the parameter is effect the level of machining performances in order to get the optimum value.
| Item Type: | Undergraduates Project Papers |
|---|---|
| Additional Information: | Project paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang – 2013 |
| Uncontrolled Keywords: | Genetic algorithms |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Mechanical Engineering |
| Depositing User: | Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 29 Oct 2015 00:02 |
| Last Modified: | 09 Jul 2021 03:49 |
| URI: | http://umpir.ump.edu.my/id/eprint/8657 |
| Download Statistic: | View Download Statistics |
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