MARC details
| 000 -LEADER |
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| fixed length control field |
02235nam a2200277 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000052554 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251114204447.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
110331t2010 my a f m 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0005785(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
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| Level of rules in bibliographic description |
201905101625 |
| Level of effort used to assign nonsubject heading access points |
aida |
| Level of effort used to assign subject headings |
201110041141 |
| Level of effort used to assign classification |
Fida |
| Level of effort used to assign subject headings |
201107140042 |
| Level of effort used to assign classification |
VLOAD |
| Level of effort used to assign subject headings |
201103311720 |
| Level of effort used to assign classification |
ida |
| -- |
201103311639 |
| -- |
ida |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMP |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TA418.7 .R89 2010 rs Bc. |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Ruzaimi Zainon |
| 245 10 - TITLE STATEMENT |
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| Title |
Optimization of surface roughness in milling using neural network (NN) / |
| Statement of responsibility, etc. |
Ruzaimi Zainon |
| 246 3# - VARYING FORM OF TITLE |
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| Title proper/short title |
Optimization of surface roughness in milling using neural network (NN) |
| Medium |
[computer file] |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMP, |
| Date of publication, distribution, etc. |
2010 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xv, 74 p. : |
| Other physical details |
ill. (some col.) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 computer disc |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Project paper (Bachelor of Mechanical Engineering with Manufacturing Engineering) -- Universiti Malaysia Pahang - 2010 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Bibliography : p. 63-64 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
This thesis discuss the Optimization of surface roughness in milling using Artificial Neural Network (ANN).Response Surface Methodology (RSM) and Neural Network implemented to model the end milling process that are using coated carbide TiN as the cutting tool and aluminium 6061 as material due to predict the resulting of surface roughness. The parameters of the variables are feed, cutting speed and depth of cut while the output is surface roughness. The model is validated through a comparison of the experimental values with their predicted counterparts. A good agreement is found where RSM approaches show 83.64% accuracy which reliable to be use in Ra prediction and state the feed parameter is the most significant parameter followed by depth of cut and cutting speed influence the surface roughness. ANN technique shows 96.68% of accuracy which is feasible and applicable in the prediction value of Ra. The proved technique opens the door for a new, simple and efficient approach that could be applied to the calibration of other empirical models of machining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Surface roughness |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Response surfaces (Statistics) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Machining |