000			01962nam a2200241 a 4500
001			vtls000031305
003			KUKTEM
005			20251114204451.0
008			080828t2008 my a f m 000 0 eng|d
020			_aTHE0002063(Local)
039		9	_a201905131623 _byusri _c201111241017 _dFida _c201107132225 _dVLOAD _c200908141514 _dVLOAD _y200808281510 _zida84
040			_aUMP
090			_aQC880.4.A5 N67 2008 rs Thesis
100	0		_aNor Asiah Johan
245	1	0	_aFormulation of multivariate chart for air mass density / _cNor Asiah Johan
260			_aKuantan, Pahang : _bUMP, _c2008
300			_a41 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc
502			_aProject paper (Bachelor of Chemical Engineering) --- Universiti Malaysia Pahang - 2008
520	3		_aAs the need for control arises from the fact that there are many disturbances occur in a process manufacturing the product, statistical control chart have been developed to overcome the problems .Traditionally in process industries, univariate chart was used to monitor the disturbance .However ,this chart is not convenient enough towards data collection on the hundred variables. The purpose of this study is to formulate the multivariate chart for air mass density using Multivariate Exponentially Weighted Moving Average (MEWMA) chart and to investigate the effect of the temperature and the pressure on the control chart. The data collections were collected from the AFPT plant, while the simulations and the chart formulation will be performed using the MATLAB 7.1 Software. The MEWMA were successfully developed and the result shows that the pressure, temperature and density of the air are in-control in the process. The MEWMA can be implemented to reduce the cost and number of variables ignored during the process period. -Author
650		0	_aAir masses
650		0	_aMultivariate analysis
999			_aVIRTUA40 _c2535 _d2541
999			_aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5200*6500*6501*9992