Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function

This report presents optimization of abrasives machining of ductile cast iron using water based SiO2 nanocoolant. Conventional and nanocoolant grinding was peerformed using the precision surface grinding machine. Study was made to invetigate the effect of table speed and depth of cut towards the sur...

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Main Author:	Azma Salwani, Ab Aziz
Format:	Undergraduates Project Papers
Language:	English
Published:	2012
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/4644/ http://umpir.ump.edu.my/id/eprint/4644/ http://umpir.ump.edu.my/id/eprint/4644/1/cd6919_76.pdf

id	ump-4644
recordtype	eprints
spelling	ump-46442015-03-03T09:20:13Z http://umpir.ump.edu.my/id/eprint/4644/ Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function Azma Salwani, Ab Aziz TA Engineering (General). Civil engineering (General) This report presents optimization of abrasives machining of ductile cast iron using water based SiO2 nanocoolant. Conventional and nanocoolant grinding was peerformed using the precision surface grinding machine. Study was made to invetigate the effect of table speed and depth of cut towards the surface roughness and MRR. The best output parameters between conventional and SiO2 nanocoolant are carry out at the end of the experiment. Mathematical modeling is developed using the response surface method. Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. MLP is a gradient descent technique to minimize the error through a particular training pattern in which it adjusts the weight by a small amount at a time. From the experiment, depth of cut is directly proportional with the surface roughness but for the table speed, it is inversely proportional to the surface roughness. For the MRR, the higher the value of depth of cut, the lower the value of MRR and for the table speed is vice versa. As the conclusion, the optimize value for each parameters are obtain where the value of surface roughness and MRR itself was 0.174 µm and 0.101 3cm/s for the conventional- single pass, 0.186 µm and 0.010 cm3/s for SiO2- single pass, 0.191µm and 0.115cm3 /s for conventional-multiple pass, and 0.240µm and 0.112 cm3 /s for the SiO2 - multiple pass. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4644/1/cd6919_76.pdf Azma Salwani, Ab Aziz (2012) Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:69411&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Azma Salwani, Ab Aziz Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
description	This report presents optimization of abrasives machining of ductile cast iron using water based SiO2 nanocoolant. Conventional and nanocoolant grinding was peerformed using the precision surface grinding machine. Study was made to invetigate the effect of table speed and depth of cut towards the surface roughness and MRR. The best output parameters between conventional and SiO2 nanocoolant are carry out at the end of the experiment. Mathematical modeling is developed using the response surface method. Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. MLP is a gradient descent technique to minimize the error through a particular training pattern in which it adjusts the weight by a small amount at a time. From the experiment, depth of cut is directly proportional with the surface roughness but for the table speed, it is inversely proportional to the surface roughness. For the MRR, the higher the value of depth of cut, the lower the value of MRR and for the table speed is vice versa. As the conclusion, the optimize value for each parameters are obtain where the value of surface roughness and MRR itself was 0.174 µm and 0.101 3cm/s for the conventional- single pass, 0.186 µm and 0.010 cm3/s for SiO2- single pass, 0.191µm and 0.115cm3 /s for conventional-multiple pass, and 0.240µm and 0.112 cm3 /s for the SiO2 - multiple pass.
format	Undergraduates Project Papers
author	Azma Salwani, Ab Aziz
author_facet	Azma Salwani, Ab Aziz
author_sort	Azma Salwani, Ab Aziz
title	Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
title_short	Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
title_full	Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
title_fullStr	Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
title_full_unstemmed	Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
title_sort	optimization of abrasive machining of ductile cast iron using water based sio2 nanocoolant : a radial basis function
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/4644/ http://umpir.ump.edu.my/id/eprint/4644/ http://umpir.ump.edu.my/id/eprint/4644/1/cd6919_76.pdf
first_indexed	2023-09-18T21:59:25Z
last_indexed	2023-09-18T21:59:25Z
_version_	1777414298053640192

Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function

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