Sometimes the quality of a process is best expressed by a relationship between response
variables and explanatory variables. Checking over the time the stability of such functional …

High-dimensional data monitoring and diagnosis has recently attracted increasing attention
among researchers as well as practitioners. However, existing process monitoring methods …

This article presents the concepts, methodologies, and applications of In-Process Quality
Improvement (IPQI) in complex manufacturing systems. As opposed to traditional quality …

The use of video-imaging data for in-line process monitoring applications has become
popular in industry. In this framework, spatio-temporal statistical process monitoring methods …

Multivariate functional principal component analysis (MFPCA) is a widely used tool for
modeling and prognosis of degradation signals. However, MFPCA usually assumes …

Profile monitoring is an important tool for quality control. Most existing profile monitoring
approaches focus on monitoring a single profile. In practice, multiple profiles also widely …

Fault source diagnosis methodology is one of the key technologies of quality control and
assurance for multi-source & multi-stage manufacturing processes, especially in small …

Abstract “Big data” is a buzzword these days due to an enormous amount of data-rich
applications in different industries and research projects. In practice, big data often take the …

This paper aims at metro station clustering based on passenger flow data. Compared with
existing clustering methods that only use boarding or alighting data of each station …

High-dimensional process monitoring, which aims to raise warnings for faulty events, is a
fundamental tool in ensuring the safety of large-scale industrial systems. Over the last few …