In this paper we discuss the basic procedures for the implementation of multivariate
statistical process control via control charting. Furthermore, we review multivariate …

Abstract Generative Artificial Intelligence (AI) models such as OpenAI's ChatGPT have the
potential to revolutionize Statistical Process Control (SPC) practice, learning, and research …

We review the long-established rational subgrouping principle for determining an effective
sampling plan for process monitoring. We present some other general advice that has been …

We provide a critical outlook of the evolution of Industrial Process Monitoring (IPM) since its
introduction almost 100 years ago. Several evolution trends that have been structuring IPM …

In most statistical process control (SPC) applications, it is assumed that the quality of a
process or product can be adequately represented by the distribution of a univariate quality …

The aim of this book is to summarize major achievements in statistical profile monitoring
methods. Statistical profile monitoring can be considered as a potential subarea of statistical …

We study the phase I analysis of data when the quality of a process or product is
characterized by a linear function. We assume that simple linear regression data are …

We propose a statistical process control scheme that can be implemented in industrial
practice, in which the quality of a process can be characterized by a general linear profile …

In many quality control applications, use of a single (or several distinct) quality characteristic
(s) is insufficient to characterize the quality of a produced item. In an increasing number of …

We propose a change point approach based on the segmented regression technique for
testing the constancy of the regression parameters in a linear profile data set. Each sample …