Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach

This project was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this project is to study the effect of nanocoolant on precision surface grinding, to investigate the performance of grinding of ductile iron based on response surface method and to...

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Main Author:	Muhammad Safwan, Azmi
Format:	Undergraduates Project Papers
Language:	English
Published:	2012
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/4890/ http://umpir.ump.edu.my/id/eprint/4890/ http://umpir.ump.edu.my/id/eprint/4890/1/cd7289_70.pdf

id	ump-4890
recordtype	eprints
spelling	ump-48902015-03-03T09:21:48Z http://umpir.ump.edu.my/id/eprint/4890/ Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach Muhammad Safwan, Azmi TJ Mechanical engineering and machinery This project was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this project is to study the effect of nanocoolant on precision surface grinding, 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 TiO2nanocoolant. 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. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4890/1/cd7289_70.pdf Muhammad Safwan, Azmi (2012) Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:75468&theme=UMP2
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 Muhammad Safwan, Azmi Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
description	This project was carried out to study the effects of using nanofluids as abrasive machining coolants. The objective of this project is to study the effect of nanocoolant on precision surface grinding, 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 TiO2nanocoolant. 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	Undergraduates Project Papers
author	Muhammad Safwan, Azmi
author_facet	Muhammad Safwan, Azmi
author_sort	Muhammad Safwan, Azmi
title	Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
title_short	Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
title_full	Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
title_fullStr	Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
title_full_unstemmed	Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
title_sort	optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/4890/ http://umpir.ump.edu.my/id/eprint/4890/ http://umpir.ump.edu.my/id/eprint/4890/1/cd7289_70.pdf
first_indexed	2023-09-18T21:59:52Z
last_indexed	2023-09-18T21:59:52Z
_version_	1777414326309617664

Optimization of abrasive machining of ductile cast iron using nanoparticles : a multilayer perceptron approach

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