The complexity of modern problems turns increasingly larger in industrial environments, so
the classical process monitoring techniques have to adapt to deal with those problems. This …

The increasing availability of high-volume, high-velocity data sets, often containing variables
of different data types, brings an increasing need for monitoring tools that are designed to …

The purpose of this paper is to provide an overview and our perspective of recent research
and applications of statistical process monitoring. The focus is on work done over the past …

One of the common problems of organizations with turn-key projects is the high scrap rate.
There exist such traditional methods as Lean Six Sigma (LSS) and DMAIC tools that analyze …

This paper presents a smart supervisory framework for a single process controller, designed
for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process …

In many applied and industrial settings, the use of Artificial Intelligence (AI) for quality
technology is gaining growing attention. AI refers to the broad set of techniques which …

Anomaly detection for processes with closed-loop control has become a widespread need in
Industry 4.0 shop floors. A major challenge in monitoring such processes arises from the …

This article explores how measurement systems having correlated characteristics are
analyzed through studies of gage repeatability and reproducibility (GR&R). The main …

The primary objective of this study is to propose and verify a new synergistic prediction-
based multivariate process quality control (MPQC) approach for manufacturing processes …

A multiple stream process (MSP) is a process at a point in time that generates several
streams of output with quality variables and specifications that are identical in all streams …