This paper compares the performance of two multivariate methods, based on
Multivariate Cumulative Sum (MCUSUM) quality control chart and generalized
variance S quality control chart. MCUSUM control charts are widely used in
industry because they are powerful and easy to use. They cumulate recent
process data to quickly detect out-of-control situations. MCUSUM procedures
will usually give tighter process control than classical quality control charts. A
MCUSUM signal does not mean that the process is producing bad product.
Rather it means that action should be taken so that the process does not
produce bad product. MCUSUM procedures give an early indication of process
change, they are consistent with a management philosophy that encourages
doing it right the first time (Pignatiello and Kasunic [25]). MCUSUM charts
tend to have inertia that later data points carry with them. As a result, when a
trend occurs on one direction of the target mean and a resulting shift occurs in
the other direction of the target mean, the two types of charts will not pick up
the shift immediately. Generalized variance S quality control chart is very
powerful way to detect small shifts in the mean vector. The main purpose of this
paper, presents an improved the generalized variance S quality control chart
for multivariate process. Generalized variance chart allow us to simultaneously
monitor whether joint variability of two or more related variables is in control.
In addition, a control chart commonly requires samples with fixed size be taken
at fixed intervals. It is assumed that in both univariate and multivariate control
charts, each sample is independent of the previous samples. Thus, this paper
decides comparison of MCUSUM and generalized variance S multivariate
control chart procedure that there is a strong need for an applied work on the
practical development and application study by real data. |
