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Warpage analysis of thick shell part (thickness above 2mm) by using response surface methodology (RSM) and glowworm swarm optimization (GSO)
Mapping Intimacies
◽
10.1063/1.5118206
◽
2019
◽
Author(s):
Y. S. Sim
◽
S. M. Nasir
◽
M. Fathullah
◽
N. A. Shuaib
◽
M. H. M. Hazwan
Keyword(s):
Response Surface Methodology
◽
Response Surface
◽
Thick Shell
◽
Swarm Optimization
◽
Glowworm Swarm Optimization
◽
Part Thickness
◽
Shell Part
Download Full-text
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Cited By
References
Warpage analysis of thick shell part (thickness above 2mm) by using response surface methodology (RSM)
10.1063/1.5118208
◽
2019
◽
Author(s):
Y. S. Sim
◽
S. M. Nasir
◽
M. Fathullah
◽
A. R. Irfan
◽
N. A. Shuaib
Keyword(s):
Response Surface Methodology
◽
Response Surface
◽
Thick Shell
◽
Part Thickness
◽
Shell Part
Download Full-text
Warpage optimization on thick shell part (thickness below 2mm) by using response surface methodology (RSM)
10.1063/1.5066799
◽
2018
◽
Cited By ~ 1
Author(s):
M. Ilyas
◽
S. M. Nasir
◽
M. Fathullah
◽
N. Z. Noriman
◽
M. H. M. Hazwan
Keyword(s):
Response Surface Methodology
◽
Response Surface
◽
Thick Shell
◽
Part Thickness
◽
Warpage Optimization
◽
Shell Part
Download Full-text
Warpage analysis of thick shell part (thickness above 2mm) by using response surface methodology (RSM) and genetic algorithm (GA)
10.1063/1.5118210
◽
2019
◽
Author(s):
Y. S. Sim
◽
S. M. Nasir
◽
M. Fathullah
◽
A. R. Irfan
◽
M. H. M. Hazwan
Keyword(s):
Genetic Algorithm
◽
Response Surface Methodology
◽
Response Surface
◽
Thick Shell
◽
Part Thickness
◽
Shell Part
Download Full-text
Deploying response surface methodology (RSM) and glowworm swarm optimization (GSO) in optimizing warpage on a mobile phone cover
10.1063/1.5002241
◽
2017
◽
Cited By ~ 1
Author(s):
X. N. Lee
◽
M. Fathullah
◽
Z. Shayfull
◽
S. M. Nasir
◽
M. H. M. Hazwan
◽
...
Keyword(s):
Response Surface Methodology
◽
Mobile Phone
◽
Response Surface
◽
Swarm Optimization
◽
Glowworm Swarm Optimization
Download Full-text
Comparison between response surface methodology, genetic algorithm & glowworm swarm optimization in injection moulding process
10.1063/1.5066709
◽
2018
◽
Author(s):
T. M. Humaizi
◽
M. Fathullah
◽
Z. Shayfull
◽
S. M. Nasir
◽
M. Shazzuan
Keyword(s):
Genetic Algorithm
◽
Response Surface Methodology
◽
Response Surface
◽
Injection Moulding
◽
Swarm Optimization
◽
Moulding Process
◽
Glowworm Swarm Optimization
◽
Injection Moulding Process
Download Full-text
Warpage analysis on thick shell part using response surface methodology (RSM) to optimize parameter setting in injection molding process
10.1063/1.5066808
◽
2018
◽
Cited By ~ 1
Author(s):
S. Q. Ch’ng
◽
S. M. Nasir
◽
M. Fathullah
◽
N. Z. Noriman
◽
M. H. M. Hazwan
Keyword(s):
Response Surface Methodology
◽
Injection Molding
◽
Response Surface
◽
Injection Molding Process
◽
Thick Shell
◽
Parameter Setting
◽
Molding Process
◽
Shell Part
Download Full-text
Warpage analysis on thick shell part using response surface methodology (RSM) and bat algorithm (BA) to optimize parameter setting in injection molding process
10.1063/1.5066806
◽
2018
◽
Author(s):
S. Q. Ch’ng
◽
S. M. Nasir
◽
M. Fathullah
◽
N. Z. Noriman
◽
S. M. Sazli
Keyword(s):
Response Surface Methodology
◽
Injection Molding
◽
Response Surface
◽
Bat Algorithm
◽
Injection Molding Process
◽
Thick Shell
◽
Parameter Setting
◽
Molding Process
◽
Shell Part
Download Full-text
Warpage optimisation on thin shell part by using response surface methodology (RSM)
10.1063/1.5002407
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2017
◽
Author(s):
R. Norshahira
◽
Z. Shayfull
◽
S. M. Nasir
◽
M. Fathullah
◽
M. H. M. Hazwan
Keyword(s):
Response Surface Methodology
◽
Response Surface
◽
Thin Shell
◽
Shell Part
Download Full-text
Milling Parameters Optimization of Al-Li Alloy Thin-Wall Workpieces Using Response Surface Methodology and Particle Swarm Optimization
Computer Modeling in Engineering & Sciences
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10.32604/cmes.2020.010565
◽
2020
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Vol 124
(3)
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pp. 937-952
Author(s):
Haitao Yue
◽
Chenguang Guo
◽
Qiang Li
◽
Lijuan Zhao
◽
Guangbo Hao
Keyword(s):
Response Surface Methodology
◽
Particle Swarm Optimization
◽
Response Surface
◽
Particle Swarm
◽
Parameters Optimization
◽
Thin Wall
◽
Swarm Optimization
◽
Milling Parameters
Download Full-text
Sonocatalytic Tannery Effluent Degradation –Response Surface Methodology and Particle Swarm Optimization Embedded Artificial Neural Network Modeling Approach
CLEAN - Soil Air Water
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10.1002/clen.202100095
◽
2021
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pp. 2100095
Author(s):
Natarajan Arun Prem Anand
◽
Ramasamy Palani
Keyword(s):
Neural Network
◽
Artificial Neural Network
◽
Response Surface Methodology
◽
Particle Swarm Optimization
◽
Response Surface
◽
Network Modeling
◽
Neural Network Modeling
◽
Tannery Effluent
◽
Swarm Optimization
◽
Artificial Neural Network Modeling
Download Full-text
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