02337nam a2200253 a 4500 vtls000075054 KUKTEM 20251114204548.0 131007t2012 my da f m 000 0 eng d THE0002018(Local) 201905131606 yusri 201311141158 nabilah 201310231014 nabilah 201310071259 nabilah UMP QA278 .S68 2012 rs Bc. Souven Jawa Steward Gima Multivariate statistical process monitoring based on dissimilarity matrix / Souven Jawa anak Steward Gima Kuantan, Pahang : UMP, 2012 xiii, 49 p. : ill. ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2012 Bibliography : p. 35-37 This thesis mainly deals with the development of new technique in process monitoring which integrates dissimilarity matrix together with the traditional technique which is the conventional Principal Component Analysis (cPCA). From previous research, it is concluded that the cPCA technique itself is not effective when the process variables of the particular process is non-linearly correlated. Specifically, the cPCA cannot detect a change of correlation among process variables as long as the monitored indexes are inside the control limits. The new technique which is dissimilarity integrated with PCAbased Multivariate Statistical Process Monitoring (MSPM), was developed by using Matlab. By using the software, two runs are executed which are based on the traditional technique and the new technique respectively. The data used is based on the simulation of CSTR system and two faults are tested with both abrupt and incipient types of faults are taken into account. The final results are projected in form of Hotelling’s T2 and Squared Prediction Error (SPE) monitoring statistics to be analyzed. Significantly, the cPCA can detect fault introduced into the system earlier if compared to the new technique specifically for incipient faults. Nevertheless, both methods are able to perform fault detection equally well for abrupt faults. Multivariate anlaysis Principal component analysis 0 0 0 1 10000 10000 2019-09-04 0 QA278 .S68 2012 rs Bc. 0000074931 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7165 | QA278 .S68 2012 rs Bc. 0000074932 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4157 4163 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992