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 …

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 …

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 …

Both linear and nonlinear relationships may exist among process variables, and monitoring
a process with such complex relationships among variables is imperative. However …

Multivariate statistical process monitoring (MSPM) methods are significant for improving
production efficiency and enhancing safety. However, to the authors' best knowledge, there …

Process fault detection and diagnosis (FDD) is an essential tool to ensure safe production in
chemical industries. After decades of development, despite the promising performance of …

In this article, we review and discuss algorithms for adaptive data-driven soft sensing. In
order to be able to provide a comprehensive overview of the adaptation techniques …

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

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 …

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 …