Statistical process control plays a key role in today's highly competitive industrial
environment since it allows quality practitioners to timely detect out‐of‐control situations and …

In estimating the standard deviation of a normally distributed random variable, a multiple of
the sample range is often used instead of the sample standard deviation in view of the …

Control charts are an important statistical process control tool used to monitor changes in
process location and variability. This study addresses issues regarding the proper choice of …

This paper concerns the design and analysis of the standard deviation control chart with
estimated limits. We consider an extensive range of statistics to estimate the in-control …

With the advances in measurement technologies, today products and processes may have
hundreds of variables that can be monitored. As the number of variables to be monitored in …

Exponentially weighted moving average (EWMA) control charts can be designed to detect
shifts in the underlying process parameters quickly while enjoying robustness to non …

Control charts are usually implemented in two phases: the retrospective phase (phase I) and
the monitoring phase (phase II). The performance of any phase II control chart structure …

Industry 4.0 vision is bringing more challenges to quality practitioners. With advances in data
acquisition systems and lowered costs, it is not uncommon in production systems to have …

Control charts are important statistical tool used to monitor fluctuations in the process
location and dispersion parameters. The issues relating to the appropriate choice of control …

Control charts play an important role in Phase I or retrospective studies, which are essential
to establish stability and generate reference data necessary for calculation of prospective …