| 000 | 02477nam a2200253 a 4500 | ||
|---|---|---|---|
| 001 | vtls000075468 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204545.0 | ||
| 008 | 131017t2012 da f m 000 0 eng d | ||
| 020 | _aTHE0006648(Local) | ||
| 039 | 9 |
_a201905161512 _bamirul _c201311251610 _dnabilah _y201310171129 _znabilah |
|
| 040 | _aUMP | ||
| 090 | _aTJ1280 .S34 2012 rs Bc. | ||
| 100 | 0 | _aMuhammad Safwan Azmi | |
| 245 | 1 | 0 |
_aOptimization of abrasive machining of ductile cast iron using nanoparticles : _ba multilayer perceptron approach / _cMuhammad Safwan Azmi |
| 260 |
_aKuantan, Pahang : _bUMP, _c2012 |
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| 300 |
_axvi, 54 p. : _bill. ; _c30 cm. + _e1 CD-ROM |
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| 502 | _aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang – 2012 | ||
| 504 | _aBibliography : p. 53-54 | ||
| 520 | 3 | _aThis 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. | |
| 650 | 0 | _aNanoparticles | |
| 650 | 0 | _aGrinding and polishing | |
| 999 |
_aVIRTUA40 _c4085 _d4091 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992 | ||