Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant

This thesis deals with the prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant. The objective of this thesis is to find the optimum parameter which was the depth of cut, investigate the surface roughness and wear produced during experimental and d...

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Main Author:	Suganthi, Jayaraman
Format:	Undergraduates Project Papers
Language:	English
Published:	2012
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/4633/ http://umpir.ump.edu.my/id/eprint/4633/ http://umpir.ump.edu.my/id/eprint/4633/1/cd6648_85.pdf

id	ump-4633
recordtype	eprints
spelling	ump-46332015-03-03T09:20:10Z http://umpir.ump.edu.my/id/eprint/4633/ Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant Suganthi, Jayaraman TJ Mechanical engineering and machinery This thesis deals with the prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant. The objective of this thesis is to find the optimum parameter which was the depth of cut, investigate the surface roughness and wear produced during experimental and develop the prediction model with the usage of Artificial Neural Network (ANN). The work piece used was aluminium alloy and zinc oxide nanocoolant as the grinding coolant. The grinding process was carried out with the usage of silicon carbide as the grinding wheel. The design of experiment was nine experiments for each single and multi-pass. The parameter used in this study was various depth of cut. The thesis describes the effect of coolant on the surface roughness and also the wheel wear. As a result, the usage of nanocoolant lead to the decrease in the surface roughness and also the wheel wear. The 2D microstructure of the grinded material was observed to view the material condition for various depth of cut. The surface roughness for grinding process using nanocoolant has a better result compared to water based coolant. Next, the result was trained using ANN to develop the prediction model for various depth of cut. Basically, the surface roughness became constant at one point with the increasing of depth of cut, whereby plastic deformation occurs. To conclude this study, the objective of the study was achieved, 1) the optimum depth of cut was 5µm, 2) the surface roughness of the material was investigated, whereby the roughness increase with the increasing of depth of cut and 3) the prediction model was done with ANN. As for the recommendation, the usage of different type of nanocoolant with various concentration and different particle sizes may affect the surface roughness of the material and also the wear produced. Next, the usage of different type and size of wheel should be considered in order to obtain a better surface finish. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4633/1/cd6648_85.pdf Suganthi, Jayaraman (2012) Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:69319&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 Suganthi, Jayaraman Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
description	This thesis deals with the prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant. The objective of this thesis is to find the optimum parameter which was the depth of cut, investigate the surface roughness and wear produced during experimental and develop the prediction model with the usage of Artificial Neural Network (ANN). The work piece used was aluminium alloy and zinc oxide nanocoolant as the grinding coolant. The grinding process was carried out with the usage of silicon carbide as the grinding wheel. The design of experiment was nine experiments for each single and multi-pass. The parameter used in this study was various depth of cut. The thesis describes the effect of coolant on the surface roughness and also the wheel wear. As a result, the usage of nanocoolant lead to the decrease in the surface roughness and also the wheel wear. The 2D microstructure of the grinded material was observed to view the material condition for various depth of cut. The surface roughness for grinding process using nanocoolant has a better result compared to water based coolant. Next, the result was trained using ANN to develop the prediction model for various depth of cut. Basically, the surface roughness became constant at one point with the increasing of depth of cut, whereby plastic deformation occurs. To conclude this study, the objective of the study was achieved, 1) the optimum depth of cut was 5µm, 2) the surface roughness of the material was investigated, whereby the roughness increase with the increasing of depth of cut and 3) the prediction model was done with ANN. As for the recommendation, the usage of different type of nanocoolant with various concentration and different particle sizes may affect the surface roughness of the material and also the wear produced. Next, the usage of different type and size of wheel should be considered in order to obtain a better surface finish.
format	Undergraduates Project Papers
author	Suganthi, Jayaraman
author_facet	Suganthi, Jayaraman
author_sort	Suganthi, Jayaraman
title	Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
title_short	Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
title_full	Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
title_fullStr	Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
title_full_unstemmed	Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
title_sort	prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/4633/ http://umpir.ump.edu.my/id/eprint/4633/ http://umpir.ump.edu.my/id/eprint/4633/1/cd6648_85.pdf
first_indexed	2023-09-18T21:59:24Z
last_indexed	2023-09-18T21:59:24Z
_version_	1777414296685248512

Prediction of grinding machinability when grind aluminium alloy using water based zinc oxide nanocoolant

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