Fault detection and diagnosis is crucial in recent industry sector to ensure safety and
reliability, and improve the overall equipment efficiency. Moreover, fault detection and …

Multiscale PCA (MSPCA) is a well-established fault-detection and isolation (FDI) technique.
It utilizes wavelet analysis and PCA to extract important features from process data. This …

In conventional process monitoring, a latent variable model (LVM) is first learned in offline
training and the statistics related to extracted latent features and residuals are then used for …

The paper purposely describes the common inventory management strategies adopted by
food processing firms in Ghana. The paper specifically investigated the key inventory …

Correlations among variables are inherent features of a multivariate system. Making a good
use of variable correlations is important to fault detection and diagnosis (FDD). In this paper …

To achieve the desired product qualities for an operating process, the operational status
must be monitored. Operating conditions are changed because of the variability in the …

In modern complex industrial operations, timely fault detection is imperative. While statistical
process monitoring is widely used in practice, conventional approaches are usually …

The increasing scale of modern chemical plants keeps popularizing investigation as well as
application of distributed process monitoring approaches. With a goal of directly quantifying …

With a goal of timely and adaptively exploiting the inconsistency inherited in the monitored
samples of current interest, a novel dynamic process monitoring method based on just‐in …

This paper focuses on product quality control issue of polystyrene polymerization reaction
process. A novel tube‐based batch model predictive control (BMPC) strategy based on a …