Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : (Record no. 3857)

MARC details
000 -LEADER
fixed length control field 02426nam a2200241 a 4500
001 - CONTROL NUMBER
control field vtls000069411
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204537.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130418t2012 my a f m 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0005908(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905141222
Level of effort used to assign nonsubject heading access points aida
-- 201304181703
-- Fida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) TA475 .A96 2012 rs Bc.
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Azma Salwani Ab Aziz
245 10 - TITLE STATEMENT
Title Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant :
Remainder of title a radial basis function /
Statement of responsibility, etc. Azma Salwani Ab Aziz
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2012
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 58 p. :
Other physical details ill. (some col.) ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2012
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p.55-58
520 3# - SUMMARY, ETC.
Summary, etc. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Cast-iron
General subdivision Analysis
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   TA475 .A96 2012 rs Bc. 0000072783 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 6919 | TA475 .A96 2012 rs Bc. 0000072784 04/09/2019 1 04/09/2019 Final Year Report

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