Control charts are powerful tools used to monitor the quality of processes. In practice, control
chart limits are often calculated using parameter estimates from an in-control Phase I …

The usual practice in control charts is to assume that the chart parameters are known or can
be accurately estimated from in-control historical samples and the data are free from outliers …

A synthetic [Xbar] chart consists of an integration of a Shewhart [Xbar] chart and a
conforming run length chart. This type of chart has been extensively used to detect a process …

Studies on the effect of parameter estimation on control-chart performance have mostly
focused on the marginal (unconditional) run length (RL) distribution and some associated …

Although it is well known that the performance of attribute control charts decreases
significantly when the assumption of known process parameters is invalid, this assumption is …

Process monitoring through control charts is a quite popular practice in statistical process
control. From a statistical point of view, a superior control chart is the one which has an …

The VSS chart, dedicated to the detection of small to moderate mean shifts in the process,
has been investigated by several researchers under the assumption of known process …

Several recent studies have shown that the number of Phase I samples required for a Phase
II control chart with estimated parameters to perform properly may be prohibitively high …

The VSI chart has been investigated by many researchers under the assumption of known
process parameters. However, in practice, these parameters are usually unknown and it is …

When monitoring the process variability, it is a common practice that a Phase I data set is
used to estimate the unknown in-control process standard deviation σ0 or variance to set up …