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 …

Abstract Fault Diagnosis and Health Monitoring (FD-HM) for modern control systems have
been an active area of research over the last few years. Model-based FD-HM computational …

Soft sensors are widely constructed in process industry to realize process monitoring, quality
prediction, and many other important applications. With the development of hardware and …

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 …

Food security relies on the resilience of staple food crops to climatic variability and extremes,
but the climate resilience of European wheat is unknown. A diversity of responses to …

Early and accurate fault detection and diagnosis for modern manufacturing processes can
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …

This paper provides an overview and analysis of statistical process monitoring methods for
fault detection, identification and reconstruction. Several fault detection indices in the …

Simulation software based on a detailed unstructured model for penicillin production in a fed-
batch fermentor has been developed. The model extends the mechanistic model of Bajpai …

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

Principal component analysis (PCA) is the most commonly used dimensionality reduction
technique for detecting and diagnosing faults in chemical processes. Although PCA contains …