Data-driven modeling and applications in plant-wide processes have recently caught much
attention in both academy and industry. This paper provides a systematic review on data …

Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …

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 …

Data-based process monitoring has become a key technology in process industries for
safety, quality, and operation efficiency enhancement. This paper provides a timely update …

For complex industrial processes with multiple operating conditions, the traditional
multivariate process monitoring techniques such as principal component analysis (PCA) and …

In this article, a just-in-time-learning (JITL)-aided canonical correlation analysis (CCA) is
proposed for the monitoring and fault detection of multimode processes. A canonical …

In real industrial processes, factors, such as the change in manufacturing strategy and
production technology lead to the creation of multimode industrial processes and the …

Many of the current multivariate statistical process monitoring techniques (such as principal
component analysis (PCA) or partial least squares (PLS)) do not utilize the non-Gaussian …

In this paper, a new fault detection and identification scheme that is based on the global–
local structure analysis (GLSA) model is proposed. By exploiting the underlying geometrical …

In most industrials, the dynamic characteristics are very common and should be paid
enough attention for process control and monitoring purposes. As a high-order Bayesian …