We review the rapidly growing literature on auxiliary information-based (AIB) process
monitoring methods. Under this approach, there is an assumption that the auxiliary variable …

Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM)
charts are famous statistical tools, to handle special causes and to bring the process back in …

Quality control charts have been widely recognized as a potentially powerful statistical
process monitoring tool in statistical process control because of their superior ability in …

A control chart is an important statistical tool for monitoring disturbances in a statistical
process, and it is richly applied in the industrial sector, the health sector and the agricultural …

Memory control chart such as multivariate CUSUM (MCUSUM) and multivariate EWMA
(MEWMA) control charts are considered superior for the detection of small-to-moderate …

In this article, an attribute control chart is proposed when the lifetime of a product follows a
Weibull distribution, which is based on the number of failures from a truncated life test. The …

Statistical quality control charts have been widely accepted as a potentially powerful process
monitoring tool because of their excellent speed in tracking shifts in the underlying process …

Every industrial process has to encounter two types of variation in product characteristic (s)
that can be classified as common and special cause variations. These variations can exist in …

Exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts are
used to detect smaller shifts in process parameters. The usual EWMA and CUSUM charts …

Abstract In Statistical Process Control (SPC), monitoring of the process dispersion has a
major impact on the performance of processes like manufacturing, management and …