Journal of Statistics: Advances in Theory and Applications
MULTIVARIATE CONTROL CHART PROCEDURE WITH
INDUSTRIAL APPLICATIONAuthor's: M. S. Hamed, A. A. El Sayed and T. H. Abouelmagd
Pages: [103] - [142]
Received Date: November 14, 2017
Submitted by:
DOI: http://dx.doi.org/10.18642/jsata_7100121889
This paper compares the performance of two multivariate methods, based
on Multivariate Cumulative Sum (MCUSUM) quality control chart and
generalized variance 
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 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 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 multivariate control chart procedure that there
is a strong need for an applied work on the practical development and
application study by real data.
quality control, multivariate process, MCUSUM quality control chart,
generalized variance quality control chart.
