Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-
driven methods have been receiving considerably increasing attention, particularly for the …

This paper provides an overview of the recent developments in data-based techniques
focused on modern industrial applications. As one of the hottest research topics for …

The development of the Internet of Things, cloud computing, and artificial intelligence has
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …

Process monitoring is crucial for maintaining favorable operating conditions and has
received considerable attention in previous decades. Currently, a plant-wide process …

This paper provides a state-of-the-art review of the methods and applications of data-driven
fault detection and diagnosis that have been developed over the last two decades. The …

In this paper, we first study a generalized canonical correlation analysis (CCA)-based fault
detection (FD) method aiming at maximizing the fault detectability under an acceptable false …

This paper provides a comparison study on the basic data-driven methods for process
monitoring and fault diagnosis (PM–FD). Based on the review of these methods and their …

Standard partial least squares (PLS) serves as a powerful tool for key performance indicator
(KPI) monitoring in large-scale process industry for last two decades. However, the standard …

Abstract The Internet of Things benefits connectivity and functionality in industrial
environments, while Cloud Computing boosts computational capability. Hence, historical …

Partial least squares or projection to latent structures (PLS) has been used in multivariate
statistical process monitoring similar to principal component analysis. Standard PLS often …