Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach

This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial ne...

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Main Authors:	M. M., Rahman, K., Kadirgama, M. M., Noor, D., Ramasamy
Format:	Article
Language:	English English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf

id	ump-11169
recordtype	eprints
spelling	ump-111692018-09-06T01:56:42Z http://umpir.ump.edu.my/id/eprint/11169/ Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy TJ Mechanical engineering and machinery This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2 nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes. Asian Research Publishing Network (ARPN) 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf M. M., Rahman and K., Kadirgama and M. M., Noor and D., Ramasamy (2016) Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach. ARPN Journal of Engineering and Applied Sciences, 11 (4). pp. 2529-2534. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0216_3679.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
description	This study was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this study is to investigate the performance of grinding of ductile iron based on response surface method and to develop optimization model for grinding parameters using artificial neural network technique. The abrasive machining process selected was surface grinding and it was carried out two different coolants which are conventional coolant and titanium dioxide nanocoolant. The selected inputs variables are table speed, depth of cut and type of grinding pattern which are single pass and multiple pass. The selected output parameters are temperature rise, surface roughness and material removal rate. The ANOVA test has been carried out to check the adequacy of the developed mathematical model. The second order mathematical model for MRR, surface roughness and temperature rise are developed based on response surface method. The artificial neural network model has been developed and analysis the performance parameters of grinding processes using two different types of coolant including the conventional as well as TiO2 nanocoolant. The obtained results shows that nanofluids as grinding coolants produces the better surface finish, good value of material removal rate and acts effectively on minimizing grinding temperature. The developed ANN model can be used as a basis of grinding processes.
format	Article
author	M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy
author_facet	M. M., Rahman K., Kadirgama M. M., Noor D., Ramasamy
author_sort	M. M., Rahman
title	Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
title_short	Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
title_full	Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
title_fullStr	Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
title_full_unstemmed	Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach
title_sort	optimization of abrasive machining of ductile cast iron using tio2 nanoparticles: a multilayer perceptron approach
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/ http://umpir.ump.edu.my/id/eprint/11169/1/Optimization%20of%20Abrasive%20Machining%20of%20Ductile%20Cast%20Iron%20Using%20Tio2%20Nanoparticles-%20A%20Multilayer%20Perceptron%20Approach.pdf http://umpir.ump.edu.my/id/eprint/11169/7/fkm-2015-mmrahman-abrasive.pdf
first_indexed	2023-09-18T22:11:38Z
last_indexed	2023-09-18T22:11:38Z
_version_	1777415066369392640

Optimization of Abrasive Machining of Ductile Cast Iron Using Tio2 Nanoparticles: A Multilayer Perceptron Approach

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