02359nam a2200265 a 4500 vtls000075899 KUKTEM 20251114204550.0 131107t2013 my da f m 000 0 eng d THE0002027(Local) 201905131610 yusri 201311131648 nabilah 201311071508 nabilah UMP QA278.5 .F33 2013 rs Bc. Nurul Fadhilah Roslan Development of PCA-based fault detection system based on various modes of NOC models for continuous-based process / Nurul Fadhilah Roslan Kuantan, Pahang : UMP, 2013 xiv, 61 p. : ill. ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2013 Bibliography : p. 48-53 Multivariate statistical techniques are used to develop detection methodology for abnormal process behavior and diagnosis of disturbance which causing poor process performance (Raich and Cinar, 2004). Hence, this study is about the development of principal component analysis (PCA) -based fault detection system based on various modes of normal operating condition (NOC) models for continuous-based process. Detecting out-of-control status and diagnosing disturbances leading to the abnormal process operation early are crucial in minimizing product quality variations (Raich and Cinar,2004). The scope of the proposed study is to run traditionally multivariate statistical process monitoring (MSPM) by defining mode difference in variance for continuous-based process. The methodology used to identify and detection of fault which undergo two phase which phase I is off-line monitoring while phase II is on-line monitoring. As a result, it will be analyze and compared of the implementing traditional PCA of Single NOC modes and Multiple NOC modes. Particularly, this study is critically concerned more on the performance during the fault detection operations comprising both off-line and on-line applications, hence it will analyze until fault detection and comparing between two modes of NOC data. Principal component analysis Process control Statistical methods Multivariate analysis 0 0 0 1 10000 10000 2019-09-04 0 QA278.5 .F33 2013 rs Bc. 0000074805 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7102 | QA278.5 .F33 2013 rs Bc. 0000074806 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4222 4228 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992