Due to the advances in the digitalization process of the manufacturing industry and the
resulting available data, there is tremendous progress and large interest in integrating …

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 …

Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …

Fault diagnosis, which identifies the root cause of the observed out-of-control status, is
essential to counteracting or eliminating faults in industrial processes. Many conventional …

The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …

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 …

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 …

In the last two decades Soft Sensors established themselves as a valuable alternative to the
traditional means for the acquisition of critical process variables, process monitoring and …

Process fault detection and diagnosis (FDD) is a predominant task to ensure product quality
and process reliability in modern industrial systems. Those traditional FDD techniques are …

Fault detection and diagnosis (FDD) systems are developed to characterize normal
variations and detect abnormal changes in a process plant. It is always important for early …