Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach

Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach

In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting...

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Main Authors: Najiha, M. S., M. M., Rahman, K., Kadirgama
Format: Article
Language:English
Published: Universiti Malaysia Pahang 2016
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/1/fkm-2016-5_Najiha%20et%20al.pdf
id ump-16173
recordtype eprints
spelling ump-161732017-08-14T03:00:38Z http://umpir.ump.edu.my/id/eprint/16173/ Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach Najiha, M. S. M. M., Rahman K., Kadirgama TJ Mechanical engineering and machinery In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. The optimization is carried out employing a parametric model (in terms of input cutting parameters, i.e., cutting speed, feed rate, depth of cut, MQL flow rate and % volume concentration of nanofluid) and exploiting the capabilities of the MOGA-II algorithm applied to the constrained machining problem. The objective functions selected to optimize are: to minimize the surface roughness; to maximize the material removal rate; and to minimize the flank wear of the cutting tool. The output of the optimization includes several alternative optimal solutions, i.e., Pareto frontier, and the best compromised configuration of the cutting parameters is selected subject to weighted preference Universiti Malaysia Pahang 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/16173/1/fkm-2016-5_Najiha%20et%20al.pdf Najiha, M. S. and M. M., Rahman and K., Kadirgama (2016) Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach. International Journal of Automotive and Mechanical Engineering (IJAME), 13 (2). pp. 3345-3360. ISSN 1985-9325(Print); 2180-1606 (Online) https://doi.org/10.15282/ijame.13.2.2016.5.0277 DOI: 10.15282/ijame.13.2.2016.5.0277
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Najiha, M. S.
M. M., Rahman
K., Kadirgama
Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
description In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. The optimization is carried out employing a parametric model (in terms of input cutting parameters, i.e., cutting speed, feed rate, depth of cut, MQL flow rate and % volume concentration of nanofluid) and exploiting the capabilities of the MOGA-II algorithm applied to the constrained machining problem. The objective functions selected to optimize are: to minimize the surface roughness; to maximize the material removal rate; and to minimize the flank wear of the cutting tool. The output of the optimization includes several alternative optimal solutions, i.e., Pareto frontier, and the best compromised configuration of the cutting parameters is selected subject to weighted preference
format Article
author Najiha, M. S.
M. M., Rahman
K., Kadirgama
author_facet Najiha, M. S.
M. M., Rahman
K., Kadirgama
author_sort Najiha, M. S.
title Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
title_short Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
title_full Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
title_fullStr Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
title_full_unstemmed Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
title_sort parametric optimization of end milling process under minimum quantity lubrication with nanofluid as cutting medium using pareto optimality approach
publisher Universiti Malaysia Pahang
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/
http://umpir.ump.edu.my/id/eprint/16173/1/fkm-2016-5_Najiha%20et%20al.pdf
first_indexed 2023-09-18T22:21:36Z
last_indexed 2023-09-18T22:21:36Z
_version_ 1777415693644333056

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