| 000 | 02512nam a2200265 a 4500 | ||
|---|---|---|---|
| 001 | vtls000075827 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204539.0 | ||
| 008 | 131106t2013 my da f m 000 0 eng d | ||
| 020 | _aTHE0002029(Local) | ||
| 039 | 9 |
_a201905131610 _byusri _c201311121655 _dnabilah _y201311061052 _znabilah |
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| 040 | _aUMP | ||
| 090 | _aQA278.5 .H89 2013 rs Bc. | ||
| 100 | 0 | _aMohd Huzaifah Hamzah | |
| 245 | 1 | 0 |
_aImplementing PCA based on fault detection system based on selected important variables for continuous process / _cMohd Huzaifah Hamzah |
| 260 |
_aKuantan, Pahang : _bUMP, _c2013 |
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| 300 |
_axiii, 67 p. : _bill. ; _c30 cm. + _e1 CD-ROM |
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| 502 | _aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2013 | ||
| 504 | _aBibliography : p. 61-64 | ||
| 520 | 3 | _aMultivariate Statistical Process Control (MSPC) is known generally as an upgraded technique, from which, it was emerged as a result of reformation in conventional Statistical Process Control (SPC) method where MSPC technique has been widely used for fault detection and diagnosis. Currently, contribution plots are used in MSPC method as basic tools for fault diagnosis. This plot does not exactly diagnose the fault but it just provides greater insight into possible causes and thereby narrow down the search. Therefore, this research is conducted to introduce a new approach and method for detecting and diagnosing fault via correlation technique. The correlation coefficient is determined using multivariate analysis techniques that could use less number of newly formed variables to represent the original data variations without losing significant information, namely Principal Component Analysis (PCA). In order to solve these problems, the objective of this research is to develop new approaches, which can improve the performance of the present conventional MSPC methods. The new approaches have been developed, the Outline Analysis Approach for examining the distribution of Principal Component Analysis (PCA) score. The result from the conventional method and ne approach were compared based on their accuracy and sensitivity. Based on the results of the study, the new approaches generally performed better compared to the conventional approaches. | |
| 650 | 0 | _aPrincipal component analysis | |
| 650 | 0 | _aMultivariate analysis | |
| 650 | 0 |
_aProcess control _xStatistical methods |
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| 999 |
_aVIRTUA40 _c3924 _d3930 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992 | ||