| 000 | 01982ntm a2200253 a 4500 | ||
|---|---|---|---|
| 001 | vtls000083412 | ||
| 003 | KUKTEM | ||
| 005 | 20251117113235.0 | ||
| 008 | 141113t2013 my a f m 000 0 eng d | ||
| 020 | _aTHE0004992(Local) | ||
| 039 | 9 |
_a201905140855 _bSHAHRILJ _c201411241002 _dFida _c201411131456 _dariffin _c201411131455 _dariffin _y201411131344 _zariffin |
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| 040 | _aUMP | ||
| 090 | _aTS156.8 .M57 2013 r Bc. | ||
| 100 | 0 | _aMira Syahirah Abd Wahit | |
| 245 | 1 | 0 |
_aUtilizing classical scaling for fault identification based on continuous-based process / _cMira Syahirah Abd Wahit |
| 260 |
_aKuantan, Pahang : _bUMP, _c2013 |
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| 300 |
_aix, 30 p. : _bill. (some col.) ; _c30 cm. + _e1 CD-ROM |
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| 502 | _aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2013 | ||
| 504 | _aBibliography : p. 53 | ||
| 520 | 3 | _aThis study is about to develop a new method on Fault Identification using Classical Scaling. Process Monitoring is from Statistical Process Control (SPC), the statistical tool which used of statistical methods and to control of a process, by repeated sampling measurements or to predict results. It also help to determine whether the process is working properly or not. This Statistical Process Control (SPC) will forms charts with data (control charts) to shown the result. This study will develop the normal Multivariate Statistical Process Monitoring (MSPM). The data will be run as the normal Multivariate Statistical Process Monitoring (MSPM). So from the technique that used in this study such as Principal Component Analysis, Statistical Process Control and Multivariate Statistical Process Monitoring (MSPM), this study will be develop which the most faster technique that will be detecting the fault in the system used. | |
| 650 | 0 |
_aProcess control _xStatistical methods |
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| 650 | 0 |
_aQuality control _xStatistical methods |
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| 999 |
_aVIRTUA40 _c5283 _d5289 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992 | ||