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1
Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm
Published 2024“…In the second optimization process, machining parameters such as cutting speed, feed rate, and depth of cut are optimized using a multi-objective genetic algorithm to concurrently lower temperature rise and surface roughness. …”
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Thesis -
2
Optimization of turning parameters using ant colony optimization
Published 2008“…Method used for this project is Ant Colony Optimization. …”
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Undergraduates Project Papers -
3
Optimization of turning parameters using genetic algorithm method
Published 2008“…This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Undergraduates Project Papers -
4
Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm
Published 2012“…The mathematical models for the cutting temperature and surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). …”
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Proceeding Paper -
5
Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…For this project, we will verify the Firefly Algorithm (FA) into finding total profit rate by optimizing the machining parameter of milling operation and compare the effectiveness of FA with other non¬conventional method. …”
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Student Project -
6
Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey
Published 2012“…In addition, there is a gap of several machining operation parameters especially for cutting temperature optimization in turning operation using PSO and AIS.…”
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Article -
7
Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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8
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization
Published 2023“…Genetic algorithms; Optimization; Particle swarm optimization (PSO); Process control; Taguchi methods; Turning; Aisi 1045 steels; Cutting parameters; Experimental values; Genetic algorithm and particle swarm optimizations; Manufacturing industries; Optimization approach; Response surface methodology; Turning operations; Surface roughness…”
Conference Paper -
9
Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm
Published 2023“…The parameters involve during this optimization are cutting speed, feed rate, depth of cut and nose radius by using genetic algorithm optimization. …”
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Conference or Workshop Item -
10
Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…Mastercam software has been used to verify the algorithm's results by applying the optimum parameter generated by GA in the Mastercam. …”
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Conference or Workshop Item -
11
Optimization of milling parameters using ant colony optimization
Published 2008“…This method was demonstrated for the optimization of machining parameters for milling operation. …”
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Undergraduates Project Papers -
12
Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method
Published 2016“…The experiments were designed using Box Behnken Design (BBD) with three input factors: cutting speed, feeding speed and depth of cut and three machining levels.…”
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Article -
13
Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…Therefore, this paper aims to obtain optimum conditions of ethe nd milling process for three cutting inserts with multi-objective parameters using a combination of mathematical modelling and genetic algorithm. …”
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Conference or Workshop Item -
14
Optimization of Turning Parameters to Minimize Production Cost using Genetic Algorithm
Published 2009“…This paper presents the study to minimize production cost for CNC turning process by using genetic algorithm (GA) method with some modification. …”
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Conference or Workshop Item -
15
A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization
“…While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm.…”
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Book Section -
16
Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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Thesis -
17
Surface roughness optimization in end milling using the multi objective genetic algorithm approach
Published 2012“…The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). …”
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Article -
18
Optimization of Multi-Pass Pocket Milling Parameter using Ant Colony Optimization
Published 2014“…This paper presents a study to optimize multi-pass pocket milling parameter using Ant Colony Optimization (ACO). …”
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Article -
19
Multi objective optimisation for high speed end milling using simulated annealing algorithm
Published 2015“…This paper presents the optimization of machining parameters in end milling processes by using the simulated annealing algorithm (SAA) as one of the unconventional methods in optimization. …”
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Article -
20
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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