MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS
Electro Discharge Machining Die Sinking (EDM die sinking) is one of non-conventional machining process for hardness material. The development of technology demands this process to have the ability to produce high quality product with good productivity. To fulfill this demand, optimization of machini...
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id-itb.:108792017-09-27T10:41:03ZMACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS FADLI AZHARI (NIM 13103020), M. Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/10879 Electro Discharge Machining Die Sinking (EDM die sinking) is one of non-conventional machining process for hardness material. The development of technology demands this process to have the ability to produce high quality product with good productivity. To fulfill this demand, optimization of machining process that includes several variables can be done.<p>There are many optimization techniques and methods which can be chosen, one of them is Genetic Algorithms. Genetic Algorithms belongs to a group of optimization techniques known as Evolutionary Algorithms. In this group there are three major types which are Genetic Algorithms, Evolutionary Programming, and Evolution Strategies. Among these three types, Genetic Algorithms are the most widely used, especially for complex optimization problems.When doing the optimization of machining condition, an algorithm with mathematical model are needed to calculate the optimum values of process variables so the aim of machining process can be achieved.<p>This research use Genetic Algorithms to optimize machining parameters of EDM die sinking, so the right combination of machine input variables for optimum cutting process can be achieved. The machine input variables are discharge current, pulse duration, interval duration, response speed, working voltage, lift-off duration and work duration. <br /> text |
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Electro Discharge Machining Die Sinking (EDM die sinking) is one of non-conventional machining process for hardness material. The development of technology demands this process to have the ability to produce high quality product with good productivity. To fulfill this demand, optimization of machining process that includes several variables can be done.<p>There are many optimization techniques and methods which can be chosen, one of them is Genetic Algorithms. Genetic Algorithms belongs to a group of optimization techniques known as Evolutionary Algorithms. In this group there are three major types which are Genetic Algorithms, Evolutionary Programming, and Evolution Strategies. Among these three types, Genetic Algorithms are the most widely used, especially for complex optimization problems.When doing the optimization of machining condition, an algorithm with mathematical model are needed to calculate the optimum values of process variables so the aim of machining process can be achieved.<p>This research use Genetic Algorithms to optimize machining parameters of EDM die sinking, so the right combination of machine input variables for optimum cutting process can be achieved. The machine input variables are discharge current, pulse duration, interval duration, response speed, working voltage, lift-off duration and work duration. <br />
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format |
Final Project |
author |
FADLI AZHARI (NIM 13103020), M. |
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FADLI AZHARI (NIM 13103020), M. MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
author_facet |
FADLI AZHARI (NIM 13103020), M. |
author_sort |
FADLI AZHARI (NIM 13103020), M. |
title |
MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
title_short |
MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
title_full |
MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
title_fullStr |
MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
title_full_unstemmed |
MACHINING PROCESS OPTIMIZATION OF EDM DIE SINKING USING GENETIC ALGORITHMS |
title_sort |
machining process optimization of edm die sinking using genetic algorithms |
url |
https://digilib.itb.ac.id/gdl/view/10879 |
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