Two main approaches are possible when several correlated variables must be monitored: one multivariate quality control chart or a set of univariate charts. This paper deals with the optimal design of a set of EWMA control charts to monitor the mean of several quality variables simultaneously. A specific Markov’s chain model has been developed to compute the ARL of a set of p EWMA charts. An opt...

Control charts are used to determine whether or not a manufacturing or business process is in a state of statistical control. Various schemes of the standard (Shewhart) X chart for autocorrelated data at sample sizes of 2 and 3 are developed and compared with the schemes of the same chart for IID data at various process shifts in the process mean. It is clear from the comparison that the in-con...

This paper proposes two alternative schemes for the online recognition of control chart patterns (CCPs), namely: 1 a scheme based on direct continuous recognition 2 a scheme based on ‘recognition only when necessary’. The study focuses on recognition of six CCPs plotted on the Shewhart X-bar chart, namely, random, shift-up, shift down, trend-up, trend-down and cyclic. The artificial neural netw...

Nonparametric control chart is useful when the underlying distribution is unknown, or is not likely to be normal. In this paper, we provide a sequential rank-based nonparametric adaptive EWMA (NAE) control chart for detecting the persistent shift in the location parameter. This NAE chart is a self-starting scheme and thus can be used to monitor processes at the start-up stages rather than waiti...

In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value). Usually fuzzy data (described by fuzzy random variables) do not have a distributional model available, and also the size of the fuzzy sample data is small. Based on the bootstrap methodology, we design a nonparametric S...

On-line monitoring of process variability is strategic to achieve high standards of quality and maintain at acceptable levels the number of nonconforming items. Shewhart control charts are the simplest Statistical Process Control (SPC) procedure to achieve this goal. An efficient implementation of a control chart requires the optimal selection of its design parameters. They can be selected acco...

We describe the adaptation of the decision limit cumulative sum method (cusum) to internal quality control in clinical chemistry. With the decision limit method, the cusum is interpreted against a numerical limit, rather than by use of a V-mask. The method can be readily implemented in computerized quality-control systems or manually on controls charts. We emphasize the manual application here ...