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 …

Highlights•Risk-based process safety management is now an accepted approach by the
industry.•Dynamic risk assessment is important to ensure continuous safety improvement.• …

Process monitoring is crucial for maintaining favorable operating conditions and has
received considerable attention in previous decades. Currently, a plant-wide process …

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

Kernel methods are a class of learning machines for the fast recognition of nonlinear
patterns in any data set. In this paper, the applications of kernel methods for feature …

In order to deeply exploit intrinsic data feature information hidden among the process data,
an improved kernel principal component analysis (KPCA) method is proposed, which is …

In modern chemical processes, a large number of process variables are collected and these
variables are usually intricately correlated, which makes it difficult to carry out plant-wide …

Large-scale plant-wide processes have become more common and monitoring of such
processes is imperative. This work focuses on establishing a distributed monitoring scheme …

Recent research has emphasized the successful application of canonical correlation
analysis (CCA) to perform fault detection (FD) in both static and dynamic processes with …

With the transformation and upgrading of the manufacturing industry, manufacturing systems
have become increasingly complex in terms of the structural functionality, process flows …