Control charts that are based on assumption (s) of a specific form for the underlying process
distribution are referred to as parametric control charts. There are many applications where …

We provide an overview and perspective on the Phase I collection and analysis of data for
use in process improvement and control charting. In Phase I, the focus is on understanding …

A major tool for quality control and management, statistical process control (SPC) monitors
sequential processes, such as production lines and Internet traffic, to ensure that they work …

Statistical process control (SPC) charts play a central role in quality control and
management. Many conventional SPC charts are designed under the assumption that the …

The assumption of fully known in-control distributions has long been recognized as an
idealization, at best approximately true. Recent development of normal-based change-point …

Process monitoring and fault diagnosis using profile data remains an important and
challenging problem in statistical process control (SPC). Although the analysis of profile data …

A unique approach to understanding the foundations of statistical quality control with a focus
on the latest developments in nonparametric control charting methodologies Statistical …

Nonparametric control charts are useful when the underlying process distribution is not likely
to be normal or is unknown. In this paper, we propose two nonparametric analogs of the …

Nonparametric or distribution-free charts are useful in statistical process control when there
is a lack of or limited knowledge about the underlying process distribution. Most existing …

This article considers statistical process control (SPC) of univariate processes when the
parametric form of the process distribution is unavailable. Most existing SPC procedures are …