Journal of Statistics: Advances in Theory and ApplicationsAuthor's: M. S. Hamed, Mahmoud M. Mansour and Enayat M. Abd Elrazik
Pages: [105] - [132]
Received Date: September 21, 2016
Submitted by:
DOI: http://dx.doi.org/10.18642/jsata_7100121721
Multivariate cumulative sum (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 producting 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 consistant with a management philosophy that encourages doing it right the first time (Pignatiello and Kasunic [14]). 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. Industry fertilizers is important one of the chemical industries in Egypt, so that this work concerns the fertilizers industries quality control, especially urea fertilizer with application on Delta fertilizer and chemical industries which is considered one of the leading companies the field of fertilizer production in Middle east with application of multivariate quality control procedures to achieve best one procedure for multivariate quality control. This application shows that the company should use the multivariate quality control chart to determine whether not the process is in-control because the production have several correlated variables, and the used of separate control charts is misleading because the variables jointly affect the process.
monitoring, quality control, multivariate quality control, CUSUM charts, MCUSUM control chart.
